Drilling fluid invasion prediction method and system based on invasion depth operation model

Abstract

The invention provides a drilling fluid invasion prediction method and system based on an invasion depth operation model, and the method comprises the steps: building a dynamic invasion numerical simulation model of drilling fluid based on two-phase seepage, mineralization degree ion convection and diffusion equations in combination with a mud cake dynamic growth equation and an auxiliary equation; analyzing an intrusion depth operation model meeting a standard condition in combination with a set stratum characteristic coefficient; respectively analyzing the influence of each influence parameter on the invasion depth at different time to determine primary and secondary control factors; after establishing a judgment matrix, carrying out normalization processing on the feature vectors to obtain a weight coefficient; and determining an intrusion depth prediction model comprehensively considering the pressure difference, the intrusion time, the stratum physical property and the fluid characteristic by combining the intrusion depth relationship under different pressure differences, so as to realize drilling fluid intrusion prediction for the required drilling well. According to the scheme, the problems that in the prior art, factors considered in simulation operation are not comprehensive, and accuracy is insufficient can be solved, accurate implementation intrusion data are obtained, and accurate resistivity correction and reservoir damage evaluation can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic monitoring of drilling engineering, and in particular to a method and system for predicting drilling fluid intrusion based on an intrusion depth calculation model. Background Art

[0002] During the drilling operation, the pressure of the drilling fluid column is greater than the formation pressure under the overbalance condition. The drilling fluid invades the formation and forms reservoir damage zones such as mud cake, flushing zone and transition zone near the wellbore wall, causing changes in the porosity and permeability of the reservoir, which greatly affects the production capacity of the oil and gas reservoir. At the same time, the invasion of the drilling fluid changes the original state of the formation near the wellbore, affecting the logging response and fluid identification of the reservoir. In order to accurately understand the degree of damage to the reservoir caused by the drilling fluid and the degree of influence of the drilling fluid invasion on the reservoir resistivity, it is necessary to study the invasion depth of the drilling fluid in the reservoir.

[0003] In actual research, the situation of drilling fluid invading the formation is related to the properties of mud filtrate, physical properties of formation and immersion time. It is difficult to accurately obtain the influence of drilling fluid invasion degree and depth on energy storage resistivity. The simulation methods of drilling fluid invading reservoir mainly include experimental research and numerical simulation. In terms of experiments: scholars in the field mainly use plunger rock samples or large-scale formation models (60cm) as experimental objects, and rely on physical simulation to carry out research on drilling fluid invasion mechanism analysis, logging response invasion correction, drilling fluid performance evaluation, reservoir protection, etc. (for example, simulation of oil-based drilling fluid invasion in sandstone reservoirs based on large-scale formation models, Wu Junchen et al., 2019). However, there are the following problems with this experimental research method: (1) The seepage pattern of drilling fluid filtrate in the cylindrical shape of the plunger rock sample (horizontal linear flow) is very different from the actual situation downhole (planar radial flow), and the observed drilling fluid filtrate loss law is not representative; (2) The size of the plunger core is small, and it cannot provide sufficient invasion space and radial distance to track the entire process of drilling fluid invasion from the beginning to the dynamic equilibrium; (3) The experimental time (generally less than 24 hours) is short compared with the actual drilling cycle, and the reference significance of obtaining the radial resistivity profile of the formation for constructing the logging resistivity model or permeability model is limited; (4) For large-scale formation models, the experiment is difficult, the experimental core is scarce, and the drilling fluid invasion depth experiment is difficult to be widely used and promoted, and the practicality is not strong (for example, the experimental study on the invasion depth of drilling fluid in tight sandstone in a block of the East China Sea, Zhang Haishan et al., 2017);

[0004] In terms of numerical simulation: Existing studies have established a mathematical model of drilling fluid invading permeable formations based on the drilling fluid invasion mechanism and the two-phase seepage equation of porous media, and calculated the radial distribution characteristics of fluid parameters on the invasion profile under different formation conditions. However, the accuracy of the simulation results cannot be guaranteed. At the same time, there is a lack of quantitative calculation models for the drilling fluid invasion depth and reservoir properties, fluid characteristics, and immersion time, making it difficult to conduct quantitative analysis (for example, numerical simulation and experimental research on the effect of drilling fluid invasion on reservoir resistivity, Wang Min et al., 2015). In addition, the invasion depth calculation method usually uses oil testing and pressure measurement data to calculate the accurate invasion radius or calculates the invasion depth based on rock physics models and mathematical models; however, such analysis has the following shortcomings: (1) The calculation of the drilling fluid invasion radius based on logging data, especially resistivity logging data, and the rock physics theoretical model do not consider the time effect of invasion and the dynamic change characteristics of the invasion process, and it is difficult to reflect the properties of the original formation (for example, using formation test data to calculate the reservoir mud invasion radius, Yu Chao et al., 2007); (2) The invasion depth prediction model based on seepage simulation mainly analyzes the influencing factors of the invasion depth qualitatively, but lacks a quantitative model, does not consider the time effect of invasion and the dynamic change characteristics of the invasion process, and it is difficult to reflect the properties of the original formation (for example, the prediction model of the invasion depth of drilling fluid solid phase and filtrate into the reservoir, Wang Jianhua et al., 2009; the invasion depth model of drilling fluid in cracks in tight sandstone, Lei Qiang et al., 2018).

[0005] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art known to those skilled in the art. Summary of the invention

[0006] In order to solve the above problems, the present invention provides a drilling fluid invasion prediction method based on an invasion depth calculation model, establishes a dynamic invasion numerical simulation model of drilling fluid; analyzes the invasion depth calculation model that meets standard conditions in combination with the set formation characteristic coefficient; analyzes the influence of each influencing parameter on the invasion depth at different times to determine the primary and secondary control factors; establishes a judgment matrix and then normalizes the characteristic vector to obtain the weight coefficient; determines an invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics, and is used to predict the drilling fluid invasion for the required drilling. This solution can overcome the problems of incomplete consideration of factors and insufficient accuracy in the simulation calculation of the prior art, obtain accurate implementation invasion data, and help to achieve accurate resistivity correction and reservoir damage evaluation. In one embodiment, the method includes:

[0007] The construction steps of the dynamic invasion numerical simulation model are as follows: based on the oil-water two-phase seepage equation, the ion convection and diffusion equations with different salinities, combined with the mud cake dynamic growth equation and the initial conditions and boundary conditions of the auxiliary equations, a dynamic invasion numerical simulation model of drilling fluid in the cylindrical coordinate system is established;

[0008] Depth calculation model determination step: Analyze the invasion radius that meets the set standard conditions according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and determine the invasion depth calculation model under the matching standard;

[0009] Factor influence degree analysis step: Based on the invasion depth calculation model, a single factor analysis method is used to simulate the influence of invasion depths at different times with formation physical parameters, fluid characteristic parameters and pressure difference as target analysis objects, and the main control factors and secondary control factors whose influence degrees meet the set conditions are analyzed and determined;

[0010] Weight coefficient calculation steps: Analyze the relative importance of each control factor, establish the corresponding judgment matrix based on the hierarchical analysis method, normalize the eigenvector of the judgment matrix, and obtain the weight coefficient of each control factor;

[0011] The steps of establishing the comprehensive prediction model are as follows: based on the determined weight coefficient, a quantitative prediction operation model of invasion depth, formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is determined; and then, an invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics is determined by combining the invasion depth relationship under different pressure differences;

[0012] Parameter collection steps: For wells that meet analysis requirements, obtain the formation physical parameters and fluid characteristic parameters of the corresponding blocks of the wells based on the logging data;

[0013] Drilling fluid invasion prediction step: Substitute the formation physical property parameters and fluid characteristic parameters into a pre-built invasion depth prediction model to determine the dynamic drilling fluid invasion data corresponding to the drilling.

[0014] In an optional embodiment, in the step of constructing a dynamic invasion numerical simulation model, it is assumed that the thickness of the oil layer is uniform and that the rocks and fluids in the reservoir are compressible. The mud cake growth dynamic equation is used to express the changes in the mud cake permeability and porosity with the pressure drop on the mud cake. Based on the oil-water two-phase seepage equation, a two-phase seepage equation ignoring gravity is established in a cylindrical coordinate system, and the relative permeabilities of formation water and oil are solved, thereby constructing ion convection and diffusion equations with different mineralizations in a cylindrical coordinate system.

[0015] Further, in one embodiment, in the step of constructing the dynamic invasion numerical simulation model, the two-phase seepage equation, the ion convection and diffusion equations of different salinities in the cylindrical coordinate system, and the calculation model of the formation water resistivity and the formation resistivity around the well are integrated to form the dynamic invasion numerical simulation model; the distribution calculation model of the formation water resistivity and the formation resistivity around the well is determined by the following operations:

[0016] Resistivity distribution analysis steps: Based on the corresponding equation calculation of the dynamic invasion numerical simulation model, the distribution of formation mineralization after the drilling fluid invasion is analyzed, and then combined with the formation water temperature and Archie's formula to calculate and determine the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times, and determine the distribution calculation model of the formation water resistivity and formation resistivity around the well.

[0017] Preferably, in one embodiment, the resistivity distribution analysis step includes the following operations:

[0018] Basic parameter solution steps: Use the finite difference method to solve the oil-water two-phase flow equation through the implicit pressure explicit saturation method to solve the pressure and fluid saturation after the drilling fluid invades the formation, so as to obtain the radial profiles of the wellbore pressure and saturation at different distances from the well axis at different invasion times;

[0019] The step of solving the salinity is as follows: based on the wellbore pressure and saturation radial profile, a finite difference method is used to obtain the salinity radial profile of the formation fluid at different distances from the well axis at different invasion times according to the ion convection and diffusion equation of salinity;

[0020] Resistivity distribution determination steps: Calculate the formation water resistivity and formation rock resistivity based on the formation water temperature, radial profile of formation fluid salinity and Archie's formula, and calculate and obtain the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times.

[0021] Further, in an optional embodiment, in the step of constructing the dynamic invasion numerical simulation model, the calculation model of the resistivity distribution of the formation water around the well is determined as follows:

[0022] The calculation model for determining the distribution of formation resistivity around the well is as follows:

[0023] Where: R w (r, t) represents the resistivity of the formation water around the well, T represents the formation temperature (℃), Cw(r, t) represents the mineralization of the formation water (PPm); R t (r, t) represents the resistivity of the formation rock at every point around the wellbore, S w(r, t) represents the water saturation of the formation at the invasion time t and the distance r from the well axis, a represents the lithology index, m represents the cementation index, and n represents the saturation index.

[0024] Preferably, in one embodiment, in the step of constructing the dynamic intrusion numerical simulation model, the ion convection and diffusion equations of different mineralizations in the cylindrical coordinate system are constructed as follows:

[0025]

[0026] Where: Cw represents the mineralization of formation water, Cmf represents the mineralization of mud filtrate, r represents the radial radius of the formation, p w represents water phase pressure, K represents formation permeability, K rw Represents the relative permeability of water phase, μ w represents the viscosity of water, t represents the invasion time of mud filtrate, q w Indicates water flow, S w Indicates water saturation.

[0027] Furthermore, in a preferred embodiment, the method also includes: a simulation verification step: based on historical drilling data, logging data, fluid analysis data and rock physics experimental data, the simulation calculation of the drilling fluid invasion value under formation conditions is realized according to the dynamic invasion numerical simulation model; based on the calculated radial profile of the rock resistivity around the well, according to the lateral logging principle and the logging instrument structure, the lateral logging differential and integral geometric factors are calculated, the lateral logging resistivity value is simulated, and then the simulation results are compared with the logging results to verify the calculation accuracy of the dynamic invasion numerical simulation model.

[0028] In an optional embodiment, in the depth calculation model determination step, the invasion radius that meets the set standard conditions is analyzed according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block according to the calculation standard described in the following formula, and is used as the invasion depth under the standard:

[0029] In the formula, R ri0 is the formation resistivity at the radial radius or radial distance ri from the wellbore; R rit is the formation resistivity at time t at the radial radius or radial distance ri; β is the formation characteristic coefficient corresponding to the block.

[0030] Furthermore, in one embodiment, in the factor influence degree analysis step, the process of simulating the influence on the invasion depth at different times by taking the formation physical property parameters, fluid characteristic parameters and pressure difference as target analysis objects respectively includes:

[0031] Based on fixed pressure difference conditions, the influence of formation properties and fluid characteristic parameters on the invasion depth at different invasion times is simulated; based on fixed formation properties and fluid characteristic parameters, the influence of pressure difference parameters on the invasion depth at different invasion times is simulated.

[0032] Specifically, in an optional embodiment, in the comprehensive prediction model establishment step, the quantitative prediction operation model for determining the invasion depth and formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is as follows:

[0033]

[0034] Wherein, r_invasion_unip is the invasion depth under fixed pressure difference, r_invasion_pr represents the invasion depth affected by porosity; r_invasion_pk represents the invasion depth determined by permeability; r_invasion_ps represents the invasion depth affected by water saturation; r_invasion_pv represents the invasion depth affected by formation water viscosity; the weight coefficients of porosity, permeability, saturation and fluid viscosity determined by the hierarchical analysis method are Wpor, Wpem, Wsat and Wvis respectively.

[0035] Further, in an optional embodiment, in the step of establishing a comprehensive prediction model, based on the variation law of invasion depth with invasion time under different pressure differences, the relationship between invasion depths under different pressure differences is determined in combination with Darcy's law, and the invasion depth prediction model that comprehensively considers pressure difference, invasion time, formation physical properties and fluid properties is determined in combination with the invasion depth relationship under different pressure differences as follows:

[0036]

[0037] Among them, varp and unip are different pressure differences.

[0038] Based on the application aspects of the method described in any one or more of the above embodiments, the present invention also provides a drilling fluid invasion prediction system based on an invasion depth calculation model, which executes the method described in any one or more of the above embodiments.

[0039] Compared with the closest prior art, the present invention also has the following beneficial effects:

[0040] The present invention provides a drilling fluid invasion prediction method and system based on an invasion depth calculation model. The method is based on a two-phase seepage equation, a salinity ion convection and diffusion equation, and combines a mud cake dynamic growth equation and an auxiliary equation to establish a dynamic invasion numerical simulation model of drilling fluid. The method fully considers the characteristics of the plane radial flow in the actual well, does not require a large-scale model test, and has high operational feasibility.

[0041] According to the invasion time, formation resistivity and set formation characteristic coefficients, an invasion depth calculation model that meets the set standard conditions is analyzed; the influence of various physical parameters, fluid characteristic parameters and pressure difference on the invasion depth at different times is analyzed separately to determine the primary and secondary control factors; based on the hierarchical analysis method, a corresponding judgment matrix is ​​established, and the characteristic vector of the matrix is ​​normalized to obtain the weight coefficient of each factor; then a quantitative prediction operation model of the invasion depth under a fixed pressure difference is determined, and the invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics is determined in combination with the invasion depth relationship under different pressure differences. The present invention considers the invasion time effect and the dynamic changes of the invasion process, and curve fitting is used to determine the invasion influence law. Then the hierarchical analysis method is used to analyze the weights of various influencing factors, and an invasion depth prediction model that comprehensively considers formation physical properties, fluid characteristics, pressure difference and immersion time is formed to achieve accurate real-time drilling fluid invasion data prediction;

[0042] In addition, the present invention effectively realizes the numerical simulation of the drilling fluid invasion process and the logging resistivity simulation, which is helpful to study the influence of drilling fluid invasion on the logging response, thereby realizing resistivity correction, and provides methods and ideas that can be used as reference and reference for studying the influence of drilling fluid invasion on reservoir permeability and correction, thereby providing a basis and theoretical support for the study of drilling fluid invasion on reservoir damage and logging response.

[0043] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0045] Figure 1 It is a flow chart of a drilling fluid invasion prediction method based on an invasion depth calculation model provided by an embodiment of the present invention;

[0046] Figure 2 It is a flow chart of a drilling fluid invasion prediction method based on an invasion depth calculation model provided by another embodiment of the present invention;

[0047] Figure 3 It is a schematic diagram of the distribution of the resistivity radial profile at different depths as the invasion time in the drilling fluid invasion prediction method based on the invasion depth calculation model provided by the embodiment of the present invention;

[0048] Figure 4(a) is a diagram showing an example structure of a lateral logging instrument for a drilling fluid invasion prediction method based on an invasion depth calculation model provided in an embodiment of the present invention;

[0049] Figure 4 (b) is a schematic diagram of the deep and shallow lateral differential based on the lateral logging instrument structure in the drilling fluid invasion prediction method based on the invasion depth calculation model provided in an embodiment of the present invention;

[0050] Figure 4 (c) is a schematic diagram of an integral geometric factor based on a laterolog instrument structure in a drilling fluid invasion prediction method based on an invasion depth calculation model provided in an embodiment of the present invention;

[0051] Figure 5 (a) is a schematic diagram of a curve showing changes in simulated lateral logging data with immersion time in a drilling fluid invasion prediction method provided in an embodiment of the present invention;

[0052] Figure 5 (b) is a schematic diagram of the comparison between the lateral resistivity simulation result and the logging data after simulating the actual immersion time in the drilling fluid invasion prediction method provided by the embodiment of the present invention;

[0053] Figure 6 (a) Figure 6 (b) Figure 6 (c) Figure 6 (d) and Figure 6 (e) are schematic diagrams showing the influence of different values ​​of permeability, porosity, water saturation, irreducible water saturation and formation water viscosity on the invasion depth over time under the pressure difference of 2 MPa in the drilling fluid invasion prediction method provided in the embodiment of the present invention;

[0054] Figure 7 (a) Figure 7 (b) Figure 7 (c) Figure 7 (d) and Figure 7 (e) are schematic diagrams showing the influence of fixed permeability, porosity, water saturation, irreducible water saturation and formation water viscosity on the invasion depth over time under different pressure differences of 2 MPa, 4 MPa, 6 MPa and 8 MPa in the drilling fluid invasion prediction method provided in the embodiment of the present invention;

[0055] Figure 8 It is a schematic diagram of the sensitivity of permeability, porosity, saturation, and fluid viscosity under a pressure difference of 2 MPa in the drilling fluid invasion prediction method provided in an embodiment of the present invention;

[0056] Fig. 9 It is a schematic diagram of application calculation data of an invasion depth prediction model in a drilling fluid invasion prediction method based on an invasion depth calculation model provided in an embodiment of the present invention;

[0057] Fig.10 It is a structural schematic diagram of a drilling fluid intrusion prediction system based on an intrusion depth calculation model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The following will describe the implementation methods of the present invention in detail in conjunction with the accompanying drawings and embodiments, so that the implementers of the present invention can fully understand how the present invention applies technical means to solve technical problems and achieve the implementation process of technical effects and implement the present invention specifically according to the above implementation process. It should be noted that as long as there is no conflict, the various embodiments and various features of the embodiments in the present invention can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0059] Although the flowcharts describe the operations as sequential processes, many of the operations may be performed in parallel, concurrently, or simultaneously. The order of the operations may be rearranged. A process may be terminated when its operations are completed, but may also have additional steps not included in the accompanying drawings. A process may correspond to a method, function, procedure, subroutine, subprogram, etc.

[0060] Computer devices include user devices and network devices. Among them, user devices or clients include but are not limited to computers, smart phones, PDAs (Personal Digital Assistants), etc.; network devices include but are not limited to a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Computer devices can be run alone to implement the present invention, or they can be connected to the network and implement the present invention through interactive operations with other computer devices in the network. The network where the computer device is located includes but is not limited to the Internet, wide area network, metropolitan area network, local area network, VPN network, etc.

[0061] The terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "one", "one" and "item" used herein are also intended to include plural numbers. It should also be understood that the terms "include" and / or "comprise" used herein specify the existence of stated features, integers, steps, operations, units and / or components, without excluding the existence or addition of one or more other features, integers, steps, operations, units, components and / or combinations thereof.

[0062] Based on the research in the field, it is known that during the drilling operation, under the overbalance condition, the drilling fluid column pressure is greater than the formation pressure, and the drilling fluid invades the formation, forming mud cakes, flushing zones, transition zones and other reservoir damage zones near the wellbore wall, causing changes in the porosity and permeability of the reservoir, thereby greatly affecting the production capacity of the oil and gas reservoir. At the same time, the invasion of drilling fluid changes the original state of the formation near the wellbore, affecting the logging response and fluid identification of the reservoir. In order to accurately understand the degree of damage to the reservoir caused by drilling fluid and the degree of influence of drilling fluid invasion on the reservoir resistivity, it is necessary to study the invasion depth of drilling fluid in the reservoir.

[0063] The situation of drilling fluid invading the formation is related to the properties of mud filtrate, physical properties of formation and immersion time. It is difficult to accurately obtain the influence of drilling fluid invasion degree and depth on energy storage resistivity. At present, the simulation methods of drilling fluid invading reservoir mainly include experimental research and numerical simulation. In terms of experiments: scholars in the field mainly use plunger rock samples or large-scale formation models (60cm) as experimental objects, and rely on physical simulation to carry out research on drilling fluid invasion mechanism analysis, logging response invasion correction, drilling fluid performance evaluation, reservoir protection, etc. (for example, simulation of oil-based drilling fluid invasion in sandstone reservoirs based on large-scale formation models, Wu Junchen et al., 2019). However, there are the following problems with this experimental research method: (1) The seepage pattern of drilling fluid filtrate in the cylindrical shape of the plunger rock sample (horizontal linear flow) is very different from the actual situation downhole (planar radial flow), and the observed drilling fluid filtrate loss law is not representative; (2) The size of the plunger core is small, and it cannot provide sufficient invasion space and radial distance to track the entire process of drilling fluid invasion from the beginning to the dynamic equilibrium; (3) The experimental time (generally less than 24 hours) is short compared with the actual drilling cycle, and the reference significance of obtaining the radial resistivity profile of the formation for constructing the logging resistivity model or permeability model is limited; (4) For large-scale formation models, the experiment is difficult, the experimental core is scarce, and the drilling fluid invasion depth experiment is difficult to be widely used and promoted, and the practicality is not strong (for example, the experimental study on the invasion depth of drilling fluid in tight sandstone in a block of the East China Sea, Zhang Haishan et al., 2017);

[0064] In terms of numerical simulation: Existing studies have established a mathematical model of drilling fluid invading permeable formations based on the drilling fluid invasion mechanism and the two-phase seepage equation of porous media, and calculated the radial distribution characteristics of fluid parameters on the invasion profile under different formation conditions. However, the accuracy of the simulation results cannot be guaranteed. At the same time, there is a lack of quantitative calculation models for the drilling fluid invasion depth and reservoir properties, fluid characteristics, and immersion time, making it difficult to conduct quantitative analysis (for example, numerical simulation and experimental research on the effect of drilling fluid invasion on reservoir resistivity, Wang Min et al., 2015). In addition, the invasion depth calculation method usually uses oil testing and pressure measurement data to calculate the accurate invasion radius or calculates the invasion depth based on rock physics models and mathematical models; however, such analysis has the following shortcomings: (1) The calculation of the drilling fluid invasion radius based on logging data, especially resistivity logging data, and the rock physics theoretical model do not consider the time effect of invasion and the dynamic change characteristics of the invasion process, and it is difficult to reflect the properties of the original formation (for example, using formation test data to calculate the reservoir mud invasion radius, Yu Chao et al., 2007); (2) The invasion depth prediction model based on seepage simulation mainly analyzes the influencing factors of the invasion depth qualitatively, but lacks a quantitative model, does not consider the time effect of invasion and the dynamic change characteristics of the invasion process, and it is difficult to reflect the properties of the original formation (for example, the prediction model of the invasion depth of drilling fluid solid phase and filtrate into the reservoir, Wang Jianhua et al., 2009; the invasion depth model of drilling fluid in cracks in tight sandstone, Lei Qiang et al., 2018).

[0065] To solve the above problems, the present invention provides a drilling fluid invasion prediction method and system based on an invasion depth calculation model. The method studies the change of invasion depth with immersion time under different physical properties, fluid characteristics and pressure difference conditions based on drilling fluid invasion simulation, determines the main and secondary control factors based on single factor analysis, determines the invasion influence law based on curve fitting, determines the weight of each influencing factor based on hierarchical analysis method, and determines the influence of pressure difference on invasion depth based on Darcy's law, thereby establishing an invasion depth prediction model that comprehensively considers formation physical properties, fluid characteristics, pressure difference and immersion time, so as to accurately predict the drilling fluid invasion depth according to demand drilling.

[0066] Next, the detailed process of the method of the embodiment of the present invention is described in detail based on the accompanying drawings. The steps shown in the flowchart of the accompanying drawings can be executed in a computer system including a set of computer executable instructions. Although the logical order of each step is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0067] Embodiment 1

[0068] Figure 1 FIG. 1 is a flow chart showing a method for predicting drilling fluid invasion based on an invasion depth calculation model according to an embodiment of the present invention, with reference to FIG. Figure 1 It can be seen that the method includes the following steps.

[0069] The construction steps of the dynamic invasion numerical simulation model are as follows: based on the oil-water two-phase seepage equation, the ion convection and diffusion equations with different salinities, combined with the mud cake dynamic growth equation and the initial conditions and boundary conditions of the auxiliary equations, a dynamic invasion numerical simulation model of drilling fluid in the cylindrical coordinate system is established;

[0070] Depth calculation model determination step: Analyze the invasion radius that meets the set standard conditions according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and determine the invasion depth calculation model under the matching standard;

[0071] Factor influence degree analysis step: Based on the invasion depth calculation model, a single factor analysis method is used to simulate the influence of invasion depths at different times with formation physical parameters, fluid characteristic parameters and pressure difference as target analysis objects, and the main control factors and secondary control factors whose influence degrees meet the set conditions are analyzed and determined;

[0072] Weight coefficient calculation steps: Analyze the relative importance of each control factor, establish the corresponding judgment matrix based on the hierarchical analysis method, normalize the eigenvector of the judgment matrix, and obtain the weight coefficient of each control factor;

[0073] The steps of establishing the comprehensive prediction model are as follows: based on the determined weight coefficient, a quantitative prediction operation model of invasion depth, formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is determined; and then, an invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics is determined by combining the invasion depth relationship under different pressure differences;

[0074] Parameter collection steps: For wells that meet analysis requirements, obtain the formation physical parameters and fluid characteristic parameters of the corresponding blocks of the wells based on the logging data;

[0075] Drilling fluid invasion prediction step: Substitute the formation physical property parameters and fluid characteristic parameters into a pre-built invasion depth prediction model to determine the dynamic drilling fluid invasion data corresponding to the drilling.

[0076] The drilling fluid invasion prediction method based on the invasion depth calculation model provided by the embodiment of the present invention is based on the two-phase seepage equation, the convection and diffusion equations of ions with different salinities, and the mud cake growth dynamic equation. According to the auxiliary equations, initial and boundary conditions, the finite difference method is used to realize the numerical simulation of drilling fluid invasion. It can overcome the difference between the seepage morphology of drilling filtrate in the lithology in the plunger core experiment and the plane radial flow in the actual well, the plunger core experiment time is less than the drilling cycle, the core is scarce in the large-scale formation model drilling fluid invasion experiment, and the experimental difficulty is high. In addition, the present invention is based on the drilling fluid invasion The invasion depth prediction model which comprehensively considers formation physical properties, fluid properties, pressure difference and immersion time is established. It can effectively solve the problem that the invasion depth model constructed based on logging data and rock physics theoretical model does not consider the invasion time effect and the dynamic changes of the invasion process.

[0077] In a preferred embodiment, in the step of constructing a dynamic invasion numerical simulation model, it is assumed that the thickness of the oil layer is uniform and that both the rock and the fluid in the reservoir are compressible. The mud cake growth dynamic equation is used to describe the changes in the mud cake permeability and porosity with the pressure drop on the mud cake. Based on the oil-water two-phase seepage equation, a two-phase seepage equation ignoring gravity is established in a cylindrical coordinate system, and the relative permeabilities of formation water and oil are solved, thereby constructing ion convection and diffusion equations of different salinities in a cylindrical coordinate system.

[0078] In actual application, when establishing the seepage model of dynamic invasion, simplified assumptions are made for the reservoir and fluid. The basic conditions of the assumptions are: there is oil-water two-phase seepage in the reservoir, the seepage of the reservoir fluid conforms to Darcy's law; the thickness of the oil layer is uniform; and both the rock and the fluid in the reservoir are compressible. The oil-water two-phase seepage equation (Formulas 1 and 2):

[0079]

[0080]

[0081] Where: p o Indicates the oil phase pressure, p w represents water phase pressure, K represents formation permeability, K ro represents the relative permeability of the oil phase, K rw Represents the relative permeability of water phase, μ 0 Indicates the viscosity of the oil phase, μ w Indicates the viscosity of water, S 0 Indicates oil saturation, S w represents water saturation, g represents gravitational acceleration, ρ 0represents the oil phase density, ρ w represents the density of water, D represents the depth of the formation, represents the formation porosity, q 0 is the oil flow rate, q w is the water flow rate, and t is the mud filtrate invasion (immersion) time.

[0082] The auxiliary equations are shown in Equations 3 and 4: S 0 +S w =1 (3); p c =p 0 -p w (4);

[0083] The initial conditions are shown in equations 5 and 6: p(r>r w ,t)| t＝0 =p 0 (5); S(r>r w ,t)| t＝0 =S w0 (6) The boundary conditions are as follows: the model maintains a stable pressure inside and the model's outer boundary is closed, as shown in equations 7 and 8:

[0084]

[0085] The ion convection and diffusion equations for different mineralizations are:

[0086]

[0087] The initial conditions (Formula 10) and boundary conditions (Formulas 11-12) are:

[0088] C w (r)| t＝0 =C w0 (10); C w (r)| r＝rw =C mf (11); C w (r)| r＝re =C w0 (12)

[0089] The dynamic equation of mud cake growth describes the change of mud cake permeability and porosity with the pressure drop on the mud cake as follows:

[0090]

[0091] In the formula, p c It represents the capillary pressure between oil and water phases, which is S w Function of r w represents the well diameter, r represents the radial radius of the formation, S wo represents the initial formation water saturation, P0 represents the initial formation pressure; p wf represents the bottom hole pressure, r e represents the outer boundary of the model; Cw represents the mineralization of formation water, Cmf represents the mineralization of drilling fluid; p mc is the pressure drop on the mud cake, psi; K mc0 is the reference permeability of the mud cake at a pressure difference of 1 psi; v is the mud cake compression index, which is generally between 0.4 and 0.9, and v = 0 means that the mud cake is completely incompressible; φ mc0 is the reference porosity of the mud cake, determined according to formula (15), where α = net wet weight / net dry weight-1; ρ f ,ρ g are mud fluid density and particle density respectively; σ is the porosity multiplier, which is obtained from the sandstone-mudstone porosity-permeability cross-plot and is generally between 0.1 and 0.2.

[0092] Based on the two-phase seepage equation (Formulas 1 and 2), the two-phase seepage equation ignoring gravity is established in the cylindrical coordinate system, as shown in Formulas (16 and 17):

[0093]

[0094] Kro and Krw represent the relative permeabilities of formation water and oil, respectively, and are calculated using formulas (18) and (19):

[0095]

[0096] In the cylindrical coordinate system, the ion convection and diffusion equations of different mineralization degrees are:

[0097]

[0098] Where: Sw(r,t) is the water saturation, which is also a function of different invasion times t; S wi is the bound water saturation; S oi is the residual oil saturation; C w Indicates the mineralization of formation water, C mf represents the mineralization of mud filtrate, r represents the radial radius of the formation, and p w represents water phase pressure, K represents formation permeability, K rw Represents the relative permeability of water phase, μ w Indicates the viscosity of water.

[0099] Specifically, in a preferred embodiment, the two-phase seepage equation, the ion convection and diffusion equations of different salinities in the cylindrical coordinate system, and the calculation models of the formation water resistivity and the formation resistivity around the well are integrated to form a dynamic intrusion numerical simulation model; the distribution calculation model of the formation water resistivity and the formation resistivity around the well is determined by the following operations:

[0100] Resistivity distribution analysis steps: Based on the corresponding equation calculation of the dynamic invasion numerical simulation model, the distribution of formation mineralization after the drilling fluid invasion is analyzed, and then combined with the formation water temperature and Archie's formula to calculate and determine the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times, and determine the distribution calculation model of the formation water resistivity and formation resistivity around the well.

[0101] Further, in an optional embodiment, the resistivity distribution analysis step includes the following operations:

[0102] Basic parameter solution steps: Use the finite difference method to solve the oil-water two-phase flow equation through the implicit pressure explicit saturation method to solve the pressure and fluid saturation after the drilling fluid invades the formation, so as to obtain the radial profiles of the wellbore pressure and saturation at different distances from the well axis at different invasion times;

[0103] The steps of solving the salinity are as follows: Based on the radial profile of the wellbore pressure and saturation, the finite difference method is used to obtain the radial profile of the salinity of the formation fluid at different distances from the well axis at different invasion times according to the ion convection and diffusion equation of salinity;

[0104] Resistivity distribution determination steps: Calculate the formation water resistivity and formation rock resistivity based on the formation water temperature, radial profile of formation fluid salinity and Archie's formula, and calculate and obtain the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times.

[0105] In practical application, in one embodiment, in the basic parameter solving step, the oil-water two-phase seepage equation is solved by using the center point grid and the finite difference method through the implicit pressure explicit saturation method, and the pressure and fluid saturation after the drilling fluid invades the formation are solved, so as to obtain the radial profiles of the wellbore pressure and saturation at different distances ri from the well axis at different immersion (invasion) times t;

[0106] The oil phase and water phase seepage equations (Formula 16 and Formula 17) are differentially discretized using the central point grid finite difference method to obtain the difference equations for oil-water two-phase seepage (Formulas 21 and 22):

[0107]

[0108]

[0109] Among them, n represents the discrete time sequence number, and i represents the grid node sequence number.

[0110] Further, in a preferred embodiment, in the step of solving the salinity, after obtaining the radial profile of the wellbore pressure and saturation, the center point grid and the finite difference method are used to obtain the different distances r from the well axis at different immersion (invasion) times t according to the ion convection and diffusion equations of different salinities.i Radial profile of formation fluid salinity on ;

[0111] The finite difference equations of ion convection and diffusion equations with different mineralization degrees are shown in formula (23):

[0112]

[0113] By solving the pressure and water saturation from the oil-water two-phase seepage differential equation (Formulas 21 and 22), the radial distribution of formation pressure and fluid saturation at different times can be obtained. Then, the dynamic changes of formation water salinity at different times can be obtained by solving the ion convection and diffusion equations of different salinities (Formula 23).

[0114] Furthermore, a resistivity distribution determination step is performed. In an optional embodiment, after obtaining the distribution profile of formation water saturation and mineralization around the well, the resistivity of formation water and rock is calculated based on the relationship between formation water temperature, mineralization and formation water resistivity (Formula 24) and Archie's formula (Formula 25), and the radial profiles of formation water resistivity and formation resistivity around the well at different distances ri from the well axis at different immersion (intrusion) times t are obtained.

[0115] Based on the radial distribution profile of mineralization around the well and the formation temperature, the formation water resistivity R can be calculated using formula (24): w (r, t), establish the radial distribution profile of formation water resistivity around the well.

[0116]

[0117] Based on Archie's formula, the rock resistivity R is calculated according to the formation water saturation around the well and the formation water resistivity distribution profile. t (r, t) radial distribution profile, the calculation method is shown in formula 25:

[0118] Where: R w (r, t) represents the resistivity of the formation water around the well, T represents the formation temperature (℃), Cw(r, t) represents the mineralization of the formation water (PPm); R t (r, t) represents the resistivity of the formation rock at every point around the wellbore, S w (r, t) represents the water saturation of the formation at the invasion time t and the distance r from the well axis, a represents the lithology index, m represents the cementation index, and n represents the saturation index. Indicates the porosity of the formation.

[0119] The depth calculation model determination step is further performed to analyze the invasion radius that meets the set standard conditions according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and determine the invasion depth calculation model under the matching standard.

[0120] Optionally, in one embodiment, in the depth calculation model determination step, based on the drilling fluid invasion numerical simulation and the formation and fluid parameters, the drilling fluid invasion influencing factors under formation conditions and the invasion depth law are analyzed;

[0121] In actual application, based on the radial section of the wellbore resistivity, the judgment condition of the invasion depth is proposed to obtain the invasion depth; in a preferred embodiment, the invasion radius that meets the set standard conditions is analyzed according to the operation standard described in the following formula based on the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and is used as the invasion depth under the standard:

[0122]

[0123] In the formula, R ri0 is the formation resistivity at the radial radius or radial distance ri from the wellbore; R rit is the formation resistivity at time t at radial radius or radial distance ri; β is the formation characteristic coefficient corresponding to the block; β is a percentage, which can be 5%, 10%, etc. According to the characteristics of the formation in the study area, β can be selected to calculate the invasion radius r that meets this standard ri This radius is referred to as the invasion radius r_invasion under this standard.

[0124] In the embodiment of the present invention, the wellbore resistivity profile at different invasion times t and different radial distances ri from the well axis is obtained according to the Archie formula, and the mud filtrate invasion radius r_invasion is determined according to the above formula (30).

[0125] Furthermore, a factor influence degree analysis step is performed. Based on the invasion depth calculation model, a single factor analysis method is adopted to simulate the influence of invasion depths at different times with each formation physical property parameter, fluid characteristic parameter and pressure difference as the target analysis object, and the main control factors and secondary control factors whose influence degree meets the set conditions are analyzed and determined.

[0126] In a preferred embodiment, in the factor influence degree analysis step, the process of simulating the influence on the invasion depth at different times by taking the formation physical property parameters, fluid characteristic parameters and pressure difference as the target analysis objects respectively includes:

[0127] Based on fixed pressure difference conditions, the influence of formation properties and fluid characteristic parameters on the invasion depth at different invasion times is simulated; based on fixed formation properties and fluid characteristic parameters, the influence of pressure difference parameters at different invasion times on the invasion depth is simulated.

[0128] In actual application, in the step of factor influence analysis, the influence of formation physical properties, fluid characteristics, pressure difference and immersion time on invasion depth is simulated; based on formation conditions, for the influencing factors of formation porosity, permeability, initial water saturation, irreducible water saturation, formation water viscosity and pressure difference, other factors are simulated to remain unchanged, and the change of invasion depth with immersion time when a certain factor changes is analyzed.

[0129] Since the establishment process of the drilling fluid invasion depth prediction model is usually carried out after the drilling is completed, in most production processes, it is impossible to limit the parameters in the drilling process according to the requirements of the invasion depth prediction model, but the actual parameters in the drilling process are applied to the invasion depth prediction model. Therefore, the relevant formation physical parameters and fluid characteristic parameters are mainly obtained from the log files during the drilling process.

[0130] In actual application, the parameters involved can be obtained through the following channels: (1) Formation temperature and pressure data, which are generally obtained based on the formation temperature and pressure predictions in the completion geological design, and the pressure measurement sampling data in the comprehensive description of oil, gas and water in the completion geological summary report to obtain the formation pressure, formation pressure coefficient, formation temperature and geothermal gradient.

[0131] (2) Reservoir properties and saturation are generally obtained through porosity and permeability saturation tests on cores sampled from the wellbore. The logging interpretation conclusions in the completion geological summary report contain porosity, permeability and saturation data.

[0132] (3) Reservoir fluid salinity and viscosity, generally obtained through pressure sampling and formation water analysis data.

[0133] (4) Reservoir rock electrical data, which are generally obtained through rock electrical experimental data from coring of the wellbore wall.

[0134] (5) Drilling fluid pressure and salinity data are generally based on the drilling fluid usage in the completion geological summary report, as well as the logging notice and drilling fluid performance table to obtain the drilling fluid type, salinity and resistivity information, and the drilling parameter table to obtain the drilling pressure, drilling fluid temperature and formation pressure gradient.

[0135] (6) Immersion time: The immersion time is generally obtained by obtaining the drilling history in the completion geological summary report, the geological daily report, and the drilling log to obtain the date of encountering the reservoir and the date of logging.

[0136] (7) Resistivity logging instrument parameters: Obtain the type of logging resistivity instrument based on the logging project statistics table and logging field application table in the completion geological summary, and obtain the corresponding logging instrument parameters in combination with the logging supervision manual.

[0137] In an optional embodiment, the present invention determines the influence of formation physical properties and fluid characteristics on invasion depth under the same pressure difference condition by single factor analysis, and determines the main and secondary control factors;

[0138] Specifically, the influence of various parameters of formation physical properties and fluid characteristics on the invasion depth at different invasion times is simulated based on a fixed pressure difference. Under a certain fixed pressure difference, based on the changes in formation porosity, permeability, saturation, and fluid viscosity, the invasion depth changes with immersion time. The Morse classification screening method (Formula 31) is used to calculate the influencing factors of each influencing factor, and the sensitivity is determined according to the numerical value.

[0139]

[0140] In the formula, S is the sensitivity factor, and a certain influencing factor takes n values, which are X 0 ,X 1 ,…,X n-1 ; The value of the influencing factor is relative to the initial value X 0 The percentage changes are: P 0 ,P 1 ,..,P n-1 ; The n values ​​of P influencing factors correspond to the simulation output results of Y 0 ,Y 1 ,,…,Y n-1 .

[0141] Mathematical statistics and curve fitting were used to determine the variation pattern of penetration depth of different physical properties and fluid characteristics with immersion time under fixed pressure difference.

[0142] Under a fixed pressure difference, the invasion depth variation curves with immersion time t are obtained when the porosity, permeability, saturation and fluid viscosity change as a single factor. Based on the curve fitting, the variation law of the invasion depth r_invasion with time t is determined.

[0143] When the porosity Por=pr1,pr2,pr3, the invasion depth r_invasion_pr changes as follows:

[0144]

[0145] According to the porosity Por=pr1,pr2,pr3, the corresponding coefficients are (Ar1,Br1)(Ar2,Br2),(Ar3,Br3), and the quantitative relationship between the coefficients and porosity is established by curve fitting: A r =f Ar (por),B r =f Br (por) (34)

[0146] Thus, the invasion depth under the influence of porosity is established: r_invasion_pr = f Ar (por)ln(t)+f Br (por) (35)

[0147] Similarly, the invasion depth under the influence of permeability, saturation, and formation fluid viscosity is established as (Formulas 36, 37, and 38): r_invasion_pk = f Ak (pem)ln(t)+f Bk (pem) (36)

[0148] r_invasion_ps=f As (sat)ln(t)+f Bs (sat) (37)

[0149] r_invasion_pv=f Av (vis)ln(t)+f Bv (vis) (38)

[0150] Wherein: r_invasion_pk, r_invasion_ps, r_invasion_pv represent the invasion depths under the influence of permeability, saturation, and fluid viscosity, respectively; fAk and fBk are the coefficients of the invasion depth model under the influence of permeability alone; fAs and fBs are the coefficients of the invasion depth model under the influence of saturation alone; fAv and fBv are the coefficients of the invasion depth model under the influence of fluid viscosity alone.

[0151] On the other hand, based on fixed formation physical properties and fluid characteristic parameters, the influence of pressure difference parameters on invasion depth at different invasion times is simulated; when the porosity, permeability, saturation and fluid viscosity are fixed respectively, the variation of invasion depth with immersion time under different pressure differences is studied.

[0152] When the porosity Por=pr1, and the pressure difference delp=p1,p2,p3, the change law of the invasion depth r_invasion_prdp is:

[0153]

[0154] When the permeability Pem=pk1, and the pressure difference delp=p1, p2, p3, the change rule of the invasion depth r_invasion_pkdp is:

[0155]

[0156] When the saturation sat=ps1, and the pressure difference delp=p1, p2, p3, the change rule of the invasion depth r_invasion_psdp is:

[0157]

[0158] When the fluid viscosity vis=pv1, and the pressure difference delp=p1,p2,p3, the change rule of the invasion depth r_invasion_pvdp is:

[0159] Based on the variation law of invasion depth with immersion time under different pressure differences, the invasion depth relationship under different pressure differences is derived in combination with Darcy's law: during the invasion of the reservoir by drilling fluid, the movable fluid in the pores is completely occupied by the drilling fluid. Therefore, the invasion process of drilling fluid is approximately expressed by Darcy's law of single-phase flow. According to Darcy's law,

[0160] The invading drilling fluid mainly occupies the pore space, so: Q = ALφ(1-Swb-Sob) (44)

[0161] Among them, Q is the drilling fluid invasion volume; k is the reservoir permeability, A is the reservoir cross-sectional area, △P is the pressure difference, μ is the drilling fluid viscosity; L is the invasion depth; φ is the porosity, Swb is the bound water porosity, and Sob is the residual oil porosity; since bound water and residual oil cannot flow, the drilling fluid can only occupy the volume of the movable fluid in the pores.

[0162] Combining formula (43) and (44), we can obtain the calculation formula of the intrusion depth:

[0163]

[0164] The relationship between the penetration depths of different pressure differences is:

[0165] Furthermore, the weight coefficient calculation step is performed to analyze the relative importance of each control factor, a corresponding judgment matrix is ​​established based on the hierarchical analysis method, and the eigenvector of the judgment matrix is ​​normalized to obtain the weight coefficient of each control factor.

[0166] The embodiment of the present invention determines the primary and secondary factors based on the analysis of drilling fluid invasion influencing factors under formation conditions, determines the weight coefficients of each influencing factor according to the hierarchical analysis method, and establishes a drilling fluid invasion depth prediction model; in actual application, in an optional embodiment, based on the main influencing factors and secondary influencing factors determined by single factor analysis, a judgment matrix A of the hierarchical analysis method is constructed according to the main influencing factors and the secondary influencing factors; A ij Indicates the importance of influencing element i relative to influencing element j, A ji It indicates the importance of influencing element j relative to influencing element i. The importance value adopts a scale of 1-9, as shown in Table 2.

[0167]

[0168] Table 2. Scales and meanings of judgment matrix elements

[0169]

[0170] Then, the weight coefficient is solved based on the hierarchical analysis method, the eigenvector of the judgment matrix A is determined, and then the eigenvector is normalized to obtain the weight coefficient W of each parameter;

[0171] Next, the comprehensive prediction model establishment step is executed. Based on the determined weight coefficient, a quantitative prediction operation model of the invasion depth and formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is determined; then, combined with the relationship between the invasion depths under different pressure differences, an invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics is determined.

[0172] Specifically, in an optional embodiment, in the step of establishing a comprehensive prediction model, based on the weight coefficient determined by the hierarchical analysis method, a quantitative prediction operation model of the invasion depth and formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is determined as follows:

[0173]

[0174] Where r_invasion_unip is the invasion depth under a fixed pressure difference, r_invasion_pr represents the invasion depth affected by porosity; r_invasion_pk represents the invasion depth determined by permeability; r_invasion_ps represents the invasion depth affected by water saturation; r_invasion_pv represents the invasion depth affected by formation water viscosity; the weight coefficients of porosity, permeability, saturation and fluid viscosity determined by the hierarchical analysis method are: Wpor, Wpem, Wsat and Wvis.

[0175] Furthermore, in the step of establishing the comprehensive prediction model, based on the changing law of invasion depth with invasion time under different pressure differences, the invasion depth relationship under different pressure differences is determined in combination with Darcy's law. The invasion depth prediction model that comprehensively considers pressure difference, invasion time, formation physical properties and fluid characteristics is determined in combination with the invasion depth relationship under different pressure differences as follows:

[0176]

[0177] Among them, varp and unip are two different pressure differences.

[0178] In practical applications, based on the invasion depth model under the same pressure difference (Formula 47) and the invasion depth relationship under different pressure differences obtained based on Darcy's law (Formula 46), an invasion depth model that comprehensively considers the pressure difference, immersion time, formation properties and fluid characteristics is obtained.

[0179] It should be emphasized that in actual implementation, since drilling in different blocks has different address characteristics and fluid characteristics, in a preferred embodiment, the block-matching invasion depth model is obtained in a targeted manner according to the needs based on the geological physical data and fluid property data of drilling in different blocks according to the operations of the above embodiment. The various invasion depth models do not interfere with each other and can be opened to technical personnel simultaneously.

[0180] In actual application, the obtained multiple invasion depth models can be set according to the needs and stored in association with their corresponding one or more geological physical property data as indexes. When used, the technicians can directly retrieve the invasion depth model whose physical property characteristic parameters match the well to be tested according to the index.

[0181] Further, a parameter collection step is performed: for the wells that meet the analysis requirements, the formation physical property parameters and fluid characteristic parameters of the corresponding blocks of the wells are obtained according to the well logging data;

[0182] Then, through the drilling fluid invasion prediction step, the formation physical property parameters and fluid characteristic parameters are substituted into the matching invasion depth prediction model to determine the dynamic drilling fluid invasion data corresponding to the drilling.

[0183] In order to ensure accurate calculation, data such as porosity, viscosity, pressure and flow rate use unified international units or engineering units to prevent calculation confusion caused by unit differences.

[0184] During the simulation process, the relationship between fluid resistivity, mineralization and temperature is based on an empirical formula; if there is experimental data, the experimental law can be used instead of the empirical formula.

[0185] The scheme of the embodiment of the present invention can replace the drilling fluid invasion experiment that is difficult to complete in practice, and provide a new method and research idea for the study and analysis of the factors affecting drilling invasion. At the same time, the numerical simulation of the drilling fluid invasion process and the logging resistivity simulation are helpful to study the influence of drilling fluid invasion on the logging response, so as to achieve resistivity correction. This process provides a method and idea that can be used for reference and reference for studying the influence of drilling fluid invasion on reservoir permeability and correction, thereby providing a basis and theoretical support for the study of drilling fluid invasion on reservoir damage and logging response; it plays an important role in the current and future prediction of reservoir damage and logging response correction, thus laying a foundation for improving the ability to identify reservoir fluids and improve the accuracy of reservoir production capacity.

[0186] Embodiment 2:

[0187] Figure 2 FIG. 1 is a flow chart showing a method for predicting drilling fluid invasion based on an invasion depth calculation model according to an embodiment of the present invention, with reference to FIG. Figure 2 It can be seen that the method includes the following steps.

[0188] The construction steps of the dynamic invasion numerical simulation model are as follows: based on the oil-water two-phase seepage equation, the ion convection and diffusion equations with different salinities, combined with the mud cake dynamic growth equation and the initial conditions and boundary conditions of the auxiliary equations, a dynamic invasion numerical simulation model of drilling fluid in the cylindrical coordinate system is established;

[0189] Depth calculation model determination step: Analyze the invasion radius that meets the set standard conditions according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and determine the invasion depth calculation model under the matching standard;

[0190] Factor influence degree analysis step: Based on the invasion depth calculation model, a single factor analysis method is used to simulate the influence of invasion depths at different times with formation physical parameters, fluid characteristic parameters and pressure difference as target analysis objects, and the main control factors and secondary control factors whose influence degrees meet the set conditions are analyzed and determined;

[0191] Weight coefficient calculation steps: Analyze the relative importance of each control factor, establish the corresponding judgment matrix based on the hierarchical analysis method, solve the weight coefficient, normalize the eigenvector of the judgment matrix, and obtain the weight coefficient of each control factor;

[0192] The steps of establishing the comprehensive prediction model are as follows: based on the determined weight coefficient, a quantitative prediction operation model of invasion depth, formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is determined; and then, an invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics is determined by combining the invasion depth relationship under different pressure differences;

[0193] Parameter collection steps: For wells that meet analysis requirements, obtain the formation physical parameters and fluid characteristic parameters of the corresponding blocks of the wells based on the logging data;

[0194] Drilling fluid invasion prediction step: Substitute the formation physical property parameters and fluid characteristic parameters into the pre-built invasion depth prediction model to determine the dynamic drilling fluid invasion data corresponding to the drilling. Embodiment 2 is a variation of Embodiment 1, and operations corresponding to or similar to those in the above Embodiment 1 are not described in detail, and only the distinguishing technical features are described.

[0195] Preferably, in one embodiment, the method further comprises: a simulation verification step: based on historical drilling data, logging data, fluid analysis data and rock physics experimental data, the simulation operation of the drilling fluid invasion value under formation conditions is realized according to the dynamic invasion numerical simulation model; based on the calculated radial profile of the rock resistivity around the well, according to the lateral logging principle and the logging instrument structure, the lateral logging differential and integral geometric factors are calculated, the lateral logging resistivity value is simulated, and then the simulation results are compared with the logging results to verify the calculation accuracy of the dynamic invasion numerical simulation model.

[0196] In the simulation test step, the numerical simulation of drilling fluid invasion under formation conditions is realized based on the historical drilling data, logging data, fluid analysis data and rock physical experiment data. Specifically, in one embodiment, the invasion simulation parameters such as formation physical property parameters, fluid parameters, rock coefficient, immersion time, etc. are obtained based on the historical drilling data, logging data, fluid analysis data and rock electrical experiment in the study area (as shown in Table 1);

[0197] Table 1. Summary of drilling fluid invasion simulation parameters under formation conditions

[0198]

[0199]

[0200] Furthermore, the center point grid and finite difference method are used to obtain different distances r from the well axis at different immersion (invasion) times t. i Radial profile of rock resistivity around the wellbore.

[0201] According to the lateral logging principle and the structure of the logging instrument, the differential and integral geometric factors of the lateral logging are calculated to simulate the lateral logging resistivity value. 0 , the total length of the main electrode is 2L, the electrode system radius is r0 and satisfies r 0 < <L 0 ; The current flowing out of the entire electrode is I, and the main current is I 0 , the current density j is evenly distributed on the wire electrode. From the logging principle of lateral logging, it can be seen that the measured resistivity Ra can be expressed as (Formula 26):

[0202] Where U represents the potential of the electrode surface, V; I 0 Represents the main current intensity, A; k represents the lateral electrode system coefficient, m. The apparent resistivity Ra is the weighted average of the resistivity R(r) of each point on the r axis, and the weight coefficient is equal to G(r)dr, where:

[0203] It is called the radial differential geometry factor.

[0204] J(r) is called the radial integral geometry factor. Formula (26) becomes:

[0205]

[0206] The apparent resistivity Ra is the product of the resistivity of the mud cake Rm, the resistivity of the invasion zone Ri and the resistivity of the original formation R t The weighted average of and They are called geometric factors of well, invasion zone and original formation respectively. The sum of weight coefficients should be 1; then the simulation results are compared with the logging results to verify the feasibility of drilling fluid invasion simulation under formation conditions and the rationality of the simulation results.

[0207] Based on the drilling fluid invasion simulation principle, the completion summary report, geological daily report, logging operation notice, pressure sampling, drilling fluid parameter table and drilling parameter table, as well as the parameters such as the pore permeability and rock electrical experimental data of the well wall core sampling are used to simulate the drilling fluid invasion under the actual drilling string pressure and formation pressure conditions to obtain the rock resistivity profile around the well. Then, the corresponding radial integral geometric factor is calculated according to the parameters of the actual logging equipment, the logging resistivity value is simulated, and it is determined that the simulation results are basically consistent with the logging data, indicating that the above-mentioned drilling fluid invasion simulation and resistivity logging simulation formulas, parameters and simulation processes are reasonable and accurate.

[0208] If the comparison between the simulation results and the logging data does not meet the set requirements, multi-angle optimization can be achieved from the following aspects:

[0209] First of all, considering that the simulation results are controlled by equations and boundary conditions, it is necessary to first confirm that the drilling fluid invasion process in the study area can approximately meet the assumptions and conditions of the Darcy seepage equation, so as to ensure the correctness of the simulation results. On this basis, it is necessary to confirm whether the boundary conditions are effective and consistent with the actual drilling and logging process, so as to ensure the correctness of the simulation results. If the equations and boundary conditions of the seepage, ion diffusion, and resistivity simulations are correct, the simulation results should be consistent with the actual situation; if the situation in the study area is complicated and the corresponding equations cannot be met, the simulation results may deviate from the actual situation, which requires further improvement.

[0210] On the premise that the seepage equation, diffusion equation of ions of different concentrations and boundary conditions are correct, we further confirm whether the simulation parameters are correct. First, we check whether the reservoir rock parameters, reservoir fluid parameters, reservoir pressure, temperature and pressure of the drilling fluid, and logging instrument parameters of the drilling fluid invasion simulation are consistent with the actual situation to avoid errors in the simulation results caused by the simulation parameters.

[0211] If the above parameters are correct, further check whether the resistivity of the reservoir fluid, the relationship between salinity and temperature, the fluid relative permeability curve, and the relationship between reservoir rock and porosity with pressure in the drilling fluid invasion simulation process use empirical formulas or actual experimental data. If empirical formulas are used, there may be differences between the simulation results and the actual results. Experimental results can be used instead of empirical formulas.

[0212] If the reservoir simulation parameters, reservoir resistivity, and fluid flow formula are correct, but there is still an error between the simulation results and the measurement results, further check whether the use of geometric factors to simulate instrument logging resistivity is applicable in the study layer. If the study layer, pore type, core complexity, and surrounding rock influence make it impossible to simulate reservoir resistivity using radial integral geometric factors, then the modified resistivity simulation formula should be used. Alternatively, the resistivity logging response simulation formula in this layer can be used instead of the geometric factor method to achieve the logging resistivity numerical simulation results. If there is currently no resistivity logging response simulation formula for the current reservoir characteristics, the prediction of drilling fluid invasion depth in this reservoir needs further research and improvement. This embodiment of the present invention obtains simulation parameters such as formation physical properties, fluid characteristics, rock electrical parameters and immersion time of drilling fluid invasion simulation based on logging data, drilling data, core experiment data and formation fluid analysis data, obtains the radial distribution profile of wellbore resistivity through drilling fluid invasion simulation, obtains radial differential and integral geometric factors of lateral logging based on the structure of lateral logging instrument, and realizes simulation and comparison of lateral logging resistivity; it can effectively overcome the problem of lack of verification of simulation results when radial invasion profile is obtained by numerical simulation of drilling fluid invasion; before analyzing the influencing factors of drilling fluid invasion under formation conditions and studying the law of invasion depth based on numerical simulation of drilling fluid invasion and formation and fluid parameters, the established dynamic invasion simulation model is verified and optimized, so as to fundamentally avoid the deviation of calculation data caused by simulation model error, ensure the calculation accuracy, and improve the reliability of the invasion depth prediction model.

[0213] The scheme of the present invention can replace the difficult-to-complete drilling fluid invasion experiment, drilling fluid invasion numerical simulation and logging resistivity simulation, obtain accurate invasion depth, help resistivity correction and reservoir damage evaluation, and improve reservoir fluid identification ability and the accuracy of reservoir productivity evaluation.

[0214] The present invention is further described below in conjunction with examples of implementation. The scope of the present invention is not limited by the examples, but is set forth in the claims.

[0215] Implementation case: Taking the YX236 well in the northern slope structural zone of the Dongying Sag in the Jiyang Depression of Sinopec as an example, the invasion depth prediction model was proposed based on the numerical simulation of drilling fluid invasion in the sandstone reservoir 3130-3150m, and the invasion depth prediction model was used to calculate the invasion prediction of the drilling. Figure 1The present invention provides a flow chart of a drilling fluid invasion prediction method based on an invasion depth calculation model, wherein the method comprises the following steps:

[0216] Step S1 of constructing a dynamic invasion numerical simulation model: based on the oil-water two-phase seepage equation, the ion convection and diffusion equations of different salinities, combined with the mud cake dynamic growth equation and the initial conditions and boundary conditions of the auxiliary equations, a dynamic invasion numerical simulation model of drilling fluid in a cylindrical coordinate system is established; based on the two-phase seepage equation, the ion convection and diffusion equations of different salinities, the dynamic growth equation of mud cake and the mathematical model of drilling fluid invasion associated with the initial and boundary conditions, a finite difference is used to construct a dynamic invasion numerical simulation model of drilling fluid;

[0217] Specifically, based on the oil-water two-phase seepage equation, the ion convection and diffusion equations of different salinities, the mud cake dynamic growth equation, and the initial and boundary conditions of the auxiliary equations, a mathematical model of drilling fluid invasion in the cylindrical coordinate system is established;

[0218] Among them, the oil-water two-phase seepage equation ignoring the gravity effect in the cylindrical coordinate system is determined as follows (1 and 2):

[0219]

[0220] In the formula, p o Indicates the oil phase pressure, p w represents water phase pressure, K represents formation permeability, K ro represents the relative permeability of the oil phase, K rw Represents the relative permeability of water phase, μ 0 Indicates the viscosity of the oil phase, μ w Indicates the viscosity of water, S 0 Indicates oil saturation, S w represents water saturation, g represents gravitational acceleration, ρ 0 represents the oil phase density, ρ w represents the density of water, D represents the depth of the formation, represents the formation porosity, q 0 represents the oil flow rate, q w represents the water flow rate, and t represents the mud filtrate invasion time.

[0221] The convection and diffusion equations in the cylindrical coordinate system are determined as follows:

[0222] Initial and boundary conditions in cylindrical coordinates:

[0223] p(r>r w ,t)| t＝0 =p 0 (4); S(r>r w ,t)| t＝0=S w0 (5)

[0224] Where: Cw, Cmf represent the mineralization of formation water and mud filtrate respectively (ppm); r w represents the well diameter, r represents the radial radius of the formation, S wo represents the initial formation water saturation, P 0 Represents the initial formation pressure.

[0225] The boundary conditions are as follows: the model maintains a stable pressure inside and the model's outer boundary is closed:

[0226]

[0227] The dynamic equation of mud cake growth describes the change of mud cake permeability and porosity with the pressure drop on the mud cake as follows:

[0228]

[0229] In the formula, p mc is the pressure drop on the mud cake, psi; K mc0 is the mud cake reference permeability at 1 psi pressure difference, v is the mud cake compression index, generally between 0.4 and 0.9, v = 0, indicating that the mud cake is completely incompressible; φ mc0 is the reference porosity of the mud cake, given by formula (15), where α = net wet weight / net dry weight-1; ρ f ,ρ g are mud fluid density and particle density respectively; σ is the porosity multiplier, which is obtained from the sandstone-mudstone porosity-permeability cross-plot and is generally between 0.1 and 0.2.

[0230] The oil-water two-phase flow equation is solved by the implicit pressure explicit saturation method using the center point grid and finite difference method to obtain the pressure and fluid saturation after the drilling fluid invades the formation, thereby obtaining the radial profiles of the wellbore pressure and saturation at different distances ri from the well axis at different immersion (invasion) times t.

[0231] The oil phase and water phase seepage equations (Formula 1 and Formula 2) are differentially discretized using the central point grid finite difference method to obtain the difference equation of oil-water two-phase seepage (Formula 11 and 12):

[0232]

[0233]

[0234] Among them, n represents the discrete time sequence number, and i represents the grid node sequence number.

[0235] After obtaining the radial profiles of wellbore pressure and saturation, the radial profiles of formation fluid salinity at different distances ri from the well axis at different immersion (invasion) times t are obtained by using the center point grid and finite difference method based on the ion convection and diffusion equations of different salinities;

[0236] The finite difference equation of the ion convection and diffusion equation (Formula 3) with different mineralization degrees is shown in Formula (13):

[0237]

[0238] In the step of constructing the dynamic invasion numerical simulation model, the two-phase seepage equation, the ion convection and diffusion equations of different salinities in the cylindrical coordinate system, and the calculation models of the formation water resistivity and formation resistivity around the well are comprehensively constituted into the dynamic invasion numerical simulation model; the distribution calculation model of the formation water resistivity and formation resistivity around the well is determined by the following operations:

[0239] Resistivity distribution analysis steps: Based on the corresponding equation calculation of the dynamic invasion numerical simulation model, the distribution of formation mineralization after the drilling fluid invasion is analyzed, and then combined with the formation water temperature and Archie's formula to calculate and determine the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times, and determine the distribution calculation model of the formation water resistivity and formation resistivity around the well.

[0240] After obtaining the distribution profiles of formation water saturation and mineralization around the well in the resistivity distribution analysis step, the formation water and rock resistivity are calculated based on the relationship between formation water temperature, mineralization and formation water resistivity and Archie's formula, and the radial profiles of formation water resistivity and formation resistivity around the well at different distances ri from the well axis at different immersion (intrusion) times t are obtained.

[0241] Based on the radial distribution profile of mineralization around the well and the formation temperature, the formation water resistivity R can be calculated using formula (14): w (r, t), establish the radial distribution profile of the water point resistivity in the formation around the well:

[0242]

[0243] Based on Archie's formula, the rock resistivity R is calculated according to the formation water saturation around the well and the formation water resistivity distribution profile. t (r, t) radial distribution profile, the calculation method is shown in formula 15:

[0244] Where: T represents the formation temperature (℃), C w (r, t) represents the mineralization of formation water (PPm), S w(r, t) is the formation water saturation at a distance r from the well axis at the invasion time t. a represents the lithology index, m represents the cementation index, and n represents the saturation index. This is the resistivity of the formation rock at each point around the wellbore.

[0245] Further, perform the simulation verification step S2: Based on the drilling history data, logging data, fluid analysis data, and rock physics experiment data, according to the dynamic invasion numerical simulation model, realize the numerical simulation operation of the drilling fluid invasion under formation conditions. Based on the calculated radial profile of the resistivity of the rock around the well, according to the lateral logging principle and the structure of the logging tool, calculate the differential and integral geometric factors of the lateral logging, simulate the resistivity value of the lateral logging, and then compare the simulation results with the logging results to verify the calculation accuracy of the dynamic invasion numerical simulation model.

[0246] In the process of realizing the numerical simulation of the drilling fluid invasion under formation conditions based on the drilling history data, logging data, fluid analysis data, and rock physics experiment data, the following operations are included.

[0247] Step S2.1: Based on the drilling history data, logging data, fluid analysis data, and rock electricity experiments in the study area, obtain the invasion simulation parameters such as formation physical properties parameters, fluid parameters, rock coefficients, soaking time, etc. (as shown in Tables 1, 2, and 3);

[0248] Step S2.2: Adopt the central point grid and the finite difference method to obtain the radial profile of the resistivity of the rock around the well at different distances ri from the well axis at different soaking (invasion) times t (as Figure 3 shown);

[0249] Step S2.3: According to the lateral logging principle (Formulas 16 - 19) and the structure of the logging tool (as Figure 4 a), calculate the differential (as Figure 4 b) and integral geometric factors of the lateral logging (as Figure 4 c), and simulate the resistivity value of the lateral logging (as Figure 5 a);

[0250] When the total length of the lateral logging electrode system is 2L0, the total length of the main electrode is 2L, the radius of the electrode system is r0 and r0 << L0; the total current flowing out of the entire electrode is I, the main current is I0, and the current density j is evenly distributed on the line electrode. From the logging principle of the lateral logging, the measured resistivity Ra can be expressed as the following formula:

[0251] Among them, U represents the potential on the electrode surface, V; I 0 represents the main current intensity, A; k represents the lateral electrode system coefficient, m. The apparent resistivity Ra is the weighted average of the resistivities R(r) at each point on the r-axis, and the weighting coefficient is equal to G(r)dr.

[0252] Among them, It is called the radial differential geometry factor; J(r) is called the radial integral geometry factor. Based on this, formula (16) becomes:

[0253]

[0254] The apparent resistivity Ra is the weighted average of the mud cake resistivity Rm, the invasion zone resistivity Ri and the original formation resistivity Rt.

[0255] Step 2.4: Compare the simulation results with the logging results (e.g. Figure 5 b) Verify the feasibility of drilling fluid invasion simulation under formation conditions and the rationality of simulation results.

[0256] Furthermore, based on the numerical simulation of drilling fluid invasion and the formation and fluid parameters, the factors affecting drilling fluid invasion under formation conditions and the law of invasion depth are analyzed. Step S3 of determining the depth calculation model is executed: according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, the invasion radius that meets the set standard conditions is analyzed, and the invasion depth calculation model under the matching standard is determined.

[0257] Specifically, based on the radial section of the wellbore resistivity, the judgment condition of the invasion depth is proposed to obtain the invasion depth; according to the radial section of the wellbore resistivity and the relationship of the change of the resistivity in the radial direction, the invasion radius r_invasion of the mud filtrate is determined, and the selection standard is as follows:

[0258] In the formula, R ri0 is the formation resistivity at the radial radius or radial distance ri from the wellbore; Rrit is the formation resistivity at the radial radius or radial distance ri at time t; β = 10%.

[0259] Furthermore, the step S4 of analyzing the degree of influence of factors is performed. Based on the invasion depth calculation model, a single factor analysis method is adopted to simulate the influence of invasion depths at different times with the formation physical parameters, fluid characteristic parameters and pressure difference as the target analysis objects, and the main control factors and secondary control factors whose influence degrees meet the set conditions are analyzed and determined.

[0260] Specifically, the influence of formation properties, fluid characteristics, pressure difference and immersion time on invasion depth was simulated. According to the formation properties and fluid parameters of the research depth section (Table 1), the formation pressure was 19.3 MPa, the borehole pressure was 21.3 MPa, the bound water saturation Swb = 10%, the residual oil saturation Sob = 10%, the formation water viscosity was 1.0 Cp, the oil viscosity was 7.0 Cp, the permeability was 0.1 mD, the porosity was 0.06, and the water saturation was 0.25 as the basic conditions. The different permeabilities (such as Figure 6 a), porosity (e.g. Figure 6 b), water saturation (e.g. Figure 6 c), irreducible water saturation (e.g. Figure 6 d), and formation water viscosity (e.g. Figure 6 e) Effect of penetration depth with immersion time.

[0261] When the formation pressure is 19.3MPa, the bound water saturation Swb = 10%, the residual oil saturation Sob = 10%, the formation water viscosity is 2.0Cp, the oil viscosity is 7.0Cp, the permeability is 0.1mD, the porosity is 0.04, and the water saturation is 0.40 as the basic conditions, the same permeability (such as Figure 7 a), porosity (e.g. Figure 7 b), water saturation (e.g. Figure 7 c), irreducible water saturation (e.g. Figure 7 d), and formation water viscosity (e.g. Figure 7 e) Effect of penetration depth with immersion time.

[0262] Single factor analysis determines the influence of formation physical properties and fluid characteristics on invasion depth under the same pressure difference conditions, and determines the main and secondary controlling factors;

[0263] Under a fixed pressure difference of 2Mpa, based on different formation porosity, permeability, saturation, and fluid viscosity, the invasion depth changes with immersion time (e.g. Figure 6 ), use the Morse classification screening method (Formulas 21 and 22) to calculate the impact factor of each influencing factor, and determine the sensitivity based on the value (such as Figure 8 ).

[0264]

[0265] In the formula, S is the sensitive factor, a certain influencing factor takes n values, namely x0, x1,…, xn-1; the percentage change of the influencing factor value relative to the initial value x0 is: P0, P1,.., Pn-1; the n values ​​of the influencing factor P correspond to the simulation output results are Y0, Y1,,…, Yn-1.

[0266] Mathematical statistics and curve fitting determined the variation law of invasion depth with immersion time for different physical properties and fluid characteristics under fixed pressure difference; under the condition of fixed pressure difference of 2Mpa, the variation curve of invasion depth with immersion time t was obtained when the porosity, permeability, saturation and fluid viscosity changed respectively (such as Figure 6 ), based on curve fitting, the invasion depths under the influence of porosity, permeability, saturation, and formation fluid viscosity are established as (Formulas 23, 24, 25, and 26):

[0267] r_invasion_pr=f Ar (por)ln(t)+f Br (por) (23)

[0268] r_invasion_pk=f Ak (pem)ln(t)+f Bk (pem) (24)

[0269] r_invasion_ps=f As (sat)ln(t)+f Bs (sat) (25)

[0270] r_invasion_pv=f Av (vis)ln(t)+f Bv (vis) (26)

[0271] Wherein: r_invasion_pr, r_invasion_pk, r_invasion_ps, r_invasion_pv represent the invasion depths under the influence of porosity, permeability, saturation and fluid viscosity respectively; fAr and fBr are the coefficients of the invasion depth model under the influence of porosity alone; fAk and fBk are the coefficients of the invasion depth model under the influence of permeability alone; fAs and fBs are the coefficients of the invasion depth model under the influence of saturation alone; fAv and fBv are the coefficients of the invasion depth model under the influence of fluid viscosity alone; the expressions of the coefficients of the invasion depth model under the influence of porosity, permeability, saturation and fluid viscosity alone are shown in Table 3.

[0272] Then, when the porosity, permeability, saturation and fluid viscosity are fixed, the variation of invasion depth with immersion time under different pressure differences is studied; based on the variation of invasion depth with immersion time under pressure differences of 2, 4, 6, and 8 MPa (such as Figure 7As shown in Figure 2, the relationship between the invasion depths under different pressure differences is derived by combining Darcy's law: during the invasion of the reservoir by drilling fluid, the movable fluid in the pores is completely occupied by the drilling fluid. Therefore, the invasion process of the drilling fluid is approximately expressed by Darcy's law of single-phase flow. According to Darcy's law, it can be known that:

[0273] The invading drilling fluid mainly occupies the pore space, so: Q = ALφ(1-Swb-Sob) (24)

[0274] Among them, Q is the drilling fluid invasion volume; k is the reservoir permeability, A is the reservoir cross-sectional area, △P is the pressure difference, μ is the drilling fluid viscosity; L is the invasion depth; φ is the porosity, Swb is the bound water porosity, and Sob is the residual oil porosity.

[0275] Since bound water and residual oil cannot flow, the drilling fluid can only occupy the volume of movable fluid in the pores. Combining formulas (23) and (24), the approximate formula for invasion depth can be obtained:

[0276] The relationship between the penetration depths of different pressure differences is:

[0277] Furthermore, based on the primary and secondary factors determined by the analysis of the factors affecting drilling fluid invasion under formation conditions, the relative importance of each control factor is analyzed, and the corresponding judgment matrix is ​​established based on the hierarchical analysis method. The weight coefficient is solved, the eigenvector of the judgment matrix is ​​normalized, the weight coefficient of each control factor is obtained, and a drilling fluid invasion depth prediction model is established.

[0278] Specifically, based on the main and secondary factors determined by the single factor analysis, the analytic hierarchy process is used to construct the judgment matrix A of the analytic hierarchy process (as shown in Table 4); the weight coefficient is solved based on the analytic hierarchy process, and the weight coefficient W of each parameter can be obtained according to the eigenvector of the judgment matrix A, and then the eigenvector is normalized (as shown in Table 5); based on the weight coefficient determined by the analytic hierarchy process, a quantitative prediction model of the invasion depth and physical properties, fluid characteristics, and immersion time under fixed pressure difference is proposed;

[0279]

[0280] In addition, based on Darcy's law of invasion depth and fluid seepage under the same pressure difference, a quantitative prediction model of invasion depth under different pressure differences is established; based on the invasion depth model under the same pressure difference (Formula 27) and the invasion depth relationship under different pressure differences obtained based on Darcy's law (Formula 26), the invasion depth model that comprehensively considers the pressure difference, immersion time, formation and fluid characteristics is obtained:

[0281] The drilling fluid invasion depth is calculated based on the formation physical properties and fluid characteristic parameters obtained from the logging data. The invasion depth is calculated based on the actual logging data and the invasion depth calculation model (Formula 28) as follows: Fig. 9 As shown, the fifth track is the calculated invasion depth.

[0282] In actual application, for wells with analysis requirements, the formation physical parameters and fluid characteristic parameters of the corresponding blocks of the wells can be obtained based on the logging data;

[0283] Drilling fluid invasion prediction step: Substitute the formation physical property parameters and fluid characteristic parameters into a pre-built invasion depth prediction model to determine the dynamic drilling fluid invasion data corresponding to the drilling.

[0284] For the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the order of the actions described, because according to the present invention, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0285] It should be noted that in other embodiments of the present invention, the method can also combine one or more of the above embodiments to obtain a new drilling fluid invasion prediction method based on an invasion depth calculation model to achieve accurate quantitative analysis and optimized application of drilling fluid invasion data. It should be noted that based on the method in any one or more of the above embodiments of the present invention, the present invention also provides a storage medium, on which program codes that can implement the method described in any one or more of the above embodiments are stored, and when the code is executed by the operating system, the drilling fluid invasion prediction method based on the invasion depth calculation model as described above can be implemented.

[0286] Embodiment three:

[0287] The method is described in detail in the embodiments disclosed in the present invention. The method of the present invention can be implemented by various forms of devices or systems. Therefore, based on other aspects of the method described in any one or more embodiments, the present invention also provides a drilling fluid invasion prediction system based on an invasion depth calculation model, which is used to execute the drilling fluid invasion prediction method based on an invasion depth calculation model described in any one or more embodiments. Specific embodiments are given below for detailed description.

[0288] Specifically, Fig.10 FIG. 4 is a schematic diagram showing a structural diagram of a drilling fluid invasion prediction system based on an invasion depth calculation model provided in an embodiment of the present invention. Fig.10 As shown, the system includes:

[0289] Dynamic invasion numerical simulation model building module, which is configured to establish a dynamic invasion numerical simulation model of drilling fluid in a cylindrical coordinate system based on the oil-water two-phase seepage equation, the ion convection and diffusion equations of different salinities, combined with the mud cake dynamic growth equation and the initial conditions and boundary conditions of the auxiliary equations;

[0290] A depth calculation model determination module is configured to analyze the invasion radius that meets the set standard conditions according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and determine the invasion depth calculation model under the matching standard;

[0291] A factor influence degree analysis module is configured to use a single factor analysis method based on the invasion depth calculation model, and simulate the influence of different invasion depths at different times with the formation physical property parameters, fluid characteristic parameters and pressure difference as target analysis objects, and analyze and determine the main control factors and secondary control factors whose influence degrees meet the set conditions;

[0292] A weight coefficient calculation module is configured to analyze the relative importance of each control factor, establish a corresponding judgment matrix based on the hierarchical analysis method, normalize the eigenvector of the judgment matrix, and obtain the weight coefficient of each control factor;

[0293] A comprehensive prediction model building module is configured to determine a quantitative prediction operation model of invasion depth, formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference based on a determined weight coefficient; and then determine an invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics in combination with the invasion depth relationship under different pressure differences;

[0294] The parameter collection module is configured to obtain the formation physical parameters and fluid characteristic parameters of the corresponding block of the drilling according to the logging data for the drilling with analysis requirements;

[0295] The drilling fluid invasion prediction module is configured to substitute the formation physical property parameters and fluid characteristic parameters into a pre-built invasion depth prediction model to determine the dynamic drilling fluid invasion data corresponding to the drilling.

[0296] In an optional embodiment, the dynamic invasion numerical simulation model construction module is configured as follows: assuming that the thickness of the oil layer is uniform and that both the rock and the fluid in the reservoir are compressible, the mud cake growth dynamic equation is used to express the changes in the mud cake permeability and porosity with the pressure drop on the mud cake, and based on the oil-water two-phase seepage equation, a two-phase seepage equation ignoring gravity is established in a cylindrical coordinate system, the relative permeability of formation water and oil is solved, and then the ion convection and diffusion equations with different mineralizations in the cylindrical coordinate system are constructed.

[0297] Furthermore, in one embodiment, the dynamic invasion numerical simulation model construction module sets a two-phase seepage equation, an ion convection and diffusion equation of different salinities in a cylindrical coordinate system, and a calculation model of the formation water resistivity and formation resistivity around the well to comprehensively constitute a dynamic invasion numerical simulation model; the distribution calculation model of the formation water resistivity and formation resistivity around the well is calculated by the following operations:

[0298] The corresponding equation calculation based on the dynamic invasion numerical simulation model is used to analyze the distribution of formation mineralization after drilling fluid invasion. Then, the formation water temperature and Archie formula are combined to calculate the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times, and the distribution calculation model of the formation water resistivity and formation resistivity around the well is determined.

[0299] Preferably, in one embodiment, the resistivity distribution analysis module includes:

[0300] The basic parameter solving unit is configured to solve the oil-water two-phase flow equation by using the finite difference method through the implicit pressure explicit saturation method, and solve the pressure and fluid saturation after the drilling fluid invades the formation, so as to obtain the radial profiles of the pressure and saturation around the well at different distances from the well axis at different invasion times;

[0301] A salinity solving unit is configured to obtain salinity radial sections of formation fluids at different distances from the well axis at different invasion times by using a finite difference method based on the wellbore pressure and saturation radial sections and according to an ion convection and diffusion equation of salinity;

[0302] The resistivity distribution determination unit is configured to calculate the formation water resistivity and the formation rock resistivity based on the formation water temperature, the radial profile of the formation fluid salinity and the Archie formula, and to calculate and obtain the formation water resistivity and the formation resistivity around the well at different distances from the well axis at different invasion times.

[0303] Further, in an optional embodiment, the dynamic invasion numerical simulation model building module is configured to determine the calculation model of the formation water resistivity distribution around the well as follows:

[0304] The calculation model for determining the distribution of formation resistivity around the well is as follows:

[0305] Preferably, in one embodiment, the dynamic intrusion numerical simulation model construction module constructs the ion convection and diffusion equations of different mineralization degrees in the cylindrical coordinate system as follows:

[0306] Furthermore, in a preferred embodiment, the system also includes: a simulation verification module, which is configured to realize simulation calculation of drilling fluid invasion values ​​under formation conditions based on the dynamic invasion numerical simulation model based on the drilling history data, logging data, fluid analysis data and rock physics experimental data; based on the calculated radial profile of rock resistivity around the well, according to the lateral logging principle and the logging instrument structure, the lateral logging differential and integral geometric factors are calculated, the lateral logging resistivity values ​​are simulated, and then the simulation results are compared with the logging results to verify the calculation accuracy of the dynamic invasion numerical simulation model.

[0307] In an optional embodiment, the depth calculation model determination module is configured to analyze the invasion radius that meets the set standard conditions according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block according to the calculation standard described in the following formula as the invasion depth under the standard:

[0308] Furthermore, in one embodiment, the factor influence degree analysis module is configured to simulate the influence on the invasion depth at different times by taking the formation physical property parameters, fluid characteristic parameters and pressure difference as the target analysis objects respectively through the following operations:

[0309] Based on fixed pressure difference conditions, simulate the influence of formation properties and fluid characteristics parameters on invasion depth at different invasion times;

[0310] Based on fixed formation physical properties and fluid characteristic parameters, the influence of pressure difference parameters at different invasion times on the invasion depth is simulated.

[0311] Specifically, in an optional embodiment, the comprehensive prediction model building module determines the quantitative prediction operation model of the invasion depth and formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference as follows:

[0312]

[0313] Further, in an optional embodiment, the comprehensive prediction model establishment module determines the invasion depth relationship under different pressure differences based on the change law of the invasion depth with the invasion time under different pressure differences in combination with Darcy's law, and determines the invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid properties in combination with the invasion depth relationship under different pressure differences as follows:

[0314]

[0315] Among them, varp and unip are different pressure differences.

[0316] In the drilling fluid invasion prediction system based on the invasion depth calculation model provided by the embodiment of the present invention, each module or unit structure can be operated independently or in combination according to actual parameter processing requirements and analysis and calculation requirements to achieve corresponding technical effects.

[0317] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those of ordinary skill in the relevant art. It should also be understood that the terms used herein are only used for the purpose of describing specific embodiments and are not meant to be limiting. The "one embodiment" mentioned in the specification means that the specific features, structures or features described in conjunction with the embodiment are included in at least one embodiment of the present invention. Therefore, the phrase "one embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0318] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A drilling fluid invasion prediction method based on an invasion depth calculation model, characterized in that: The method comprises: The construction steps of the dynamic invasion numerical simulation model are as follows: based on the oil-water two-phase seepage equation, the ion convection and diffusion equations with different salinities, combined with the mud cake dynamic growth equation and the initial conditions and boundary conditions of the auxiliary equations, a dynamic invasion numerical simulation model of drilling fluid in the cylindrical coordinate system is established; Depth calculation model determination step: Analyze the invasion radius that meets the set standard conditions according to the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and determine the invasion depth calculation model under the matching standard; Factor influence degree analysis step: Based on the invasion depth calculation model, a single factor analysis method is used to simulate the influence of invasion depths at different times with formation physical parameters, fluid characteristic parameters and pressure difference as target analysis objects, and the main control factors and secondary control factors whose influence degrees meet the set conditions are analyzed and determined; Weight coefficient calculation steps: Analyze the relative importance of each control factor, establish the corresponding judgment matrix based on the hierarchical analysis method, normalize the eigenvector of the judgment matrix, and obtain the weight coefficient of each control factor; The steps of establishing the comprehensive prediction model are as follows: based on the determined weight coefficient, a quantitative prediction operation model of invasion depth, formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is determined; and then, an invasion depth prediction model that comprehensively considers the pressure difference, invasion time, formation physical properties and fluid characteristics is determined by combining the invasion depth relationship under different pressure differences; Parameter collection steps: For wells that meet analysis requirements, obtain the formation physical parameters and fluid characteristic parameters of the corresponding blocks of the wells based on the logging data; Drilling fluid invasion prediction step: Substitute the formation physical property parameters and fluid characteristic parameters into a pre-built invasion depth prediction model to determine the dynamic drilling fluid invasion data corresponding to the drilling.

2. The method according to claim 1, characterized in that In the construction step of the dynamic invasion numerical simulation model, it is assumed that the thickness of the oil layer is uniform and the rocks and fluids in the reservoir are compressible. The mud cake growth dynamic equation is used to express the changes in mud cake permeability and porosity with the pressure drop on the mud cake. Based on the oil-water two-phase seepage equation, a two-phase seepage equation ignoring gravity is established in the cylindrical coordinate system, and the relative permeabilities of formation water and oil are solved, and then the ion convection and diffusion equations with different salinities in the cylindrical coordinate system are constructed.

3. The method according to claim 1, characterized in that In the step of constructing the dynamic invasion numerical simulation model, the two-phase seepage equation, the ion convection and diffusion equations of different salinities in the cylindrical coordinate system, and the calculation models of the formation water resistivity and formation resistivity around the well are comprehensively constituted into the dynamic invasion numerical simulation model; the distribution calculation model of the formation water resistivity and formation resistivity around the well is determined by the following operations: Resistivity distribution analysis steps: Based on the corresponding equation calculation of the dynamic invasion numerical simulation model, the distribution of formation mineralization after the drilling fluid invasion is analyzed, and then combined with the formation water temperature and Archie's formula to calculate and determine the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times, and determine the distribution calculation model of the formation water resistivity and formation resistivity around the well.

4. The method according to claim 3, characterized in that The resistivity distribution analysis step includes the following operations: Basic parameter solution steps: Use the finite difference method to solve the oil-water two-phase flow equation through the implicit pressure explicit saturation method to solve the pressure and fluid saturation after the drilling fluid invades the formation, so as to obtain the radial profiles of the wellbore pressure and saturation at different distances from the well axis at different invasion times; The step of solving the salinity is as follows: based on the wellbore pressure and saturation radial profile, a finite difference method is used to obtain the salinity radial profile of the formation fluid at different distances from the well axis at different invasion times according to the ion convection and diffusion equation of salinity; Resistivity distribution determination steps: Calculate the formation water resistivity and formation rock resistivity based on the formation water temperature, radial profile of formation fluid salinity and Archie's formula, and calculate and obtain the formation water resistivity and formation resistivity around the well at different distances from the well axis at different invasion times.

5. The method according to claim 3, characterized in that: In the step of building the dynamic intrusion numerical simulation model, The calculation model for determining the distribution of formation water resistivity around the well is as follows: The calculation model for determining the distribution of formation resistivity around the well is as follows: Where: R w (r, t) represents the resistivity of the formation water around the well, T represents the formation temperature (℃), Cw(r, t) represents the mineralization of the formation water (PPm); R t (r, t) represents the resistivity of the formation rock at every point around the wellbore, S w (r, t) represents the water saturation of the formation at the invasion time t and the distance r from the well axis, a represents the lithology index, m represents the cementation index, and n represents the saturation index.

6. The method according to claim 1, characterized in that In the step of constructing the dynamic intrusion numerical simulation model, the ion convection and diffusion equations of different mineralization degrees in the cylindrical coordinate system are constructed as follows: Where: Cw represents the mineralization of formation water, Cmf represents the mineralization of mud filtrate, r represents the radial radius of the formation, p w represents water phase pressure, K represents formation permeability, K rw Represents the relative permeability of water phase, μ w represents the viscosity of water, t represents the invasion time of mud filtrate, q w Indicates water flow, S w Indicates water saturation.

7. The method according to claim 1, characterized in that The method further comprises: Simulation verification steps: Based on historical drilling data, logging data, fluid analysis data and rock physics experimental data, the dynamic invasion numerical simulation model is used to realize the simulation calculation of the drilling fluid invasion value under formation conditions. Based on the calculated radial profile of rock resistivity around the well, according to the lateral logging principle and the logging instrument structure, the lateral logging differential and integral geometric factors are calculated, the lateral logging resistivity value is simulated, and then the simulation results are compared with the logging results to verify the calculation accuracy of the dynamic invasion numerical simulation model.

8. The method according to claim 1, characterized in that In the depth calculation model determination step, the invasion radius that meets the set standard conditions is analyzed according to the calculation standard described in the following formula based on the invasion time and the corresponding formation resistivity combined with the set formation characteristic coefficient of the block, and is used as the invasion depth under this standard: In the formula, R ri0 is the formation resistivity at the radial radius or radial distance ri from the wellbore; R rit is the formation resistivity at time t at the radial radius or radial distance ri; β is the formation characteristic coefficient corresponding to the block.

9. The method according to claim 1, characterized in that: In the step of factor influence degree analysis, the process of simulating the influence on invasion depth at different times is carried out with formation physical parameters, fluid characteristic parameters and pressure difference as target analysis objects, including: Based on fixed pressure difference conditions, simulate the influence of formation properties and fluid characteristics parameters on invasion depth at different invasion times; Based on fixed formation physical properties and fluid characteristic parameters, the influence of pressure difference parameters on invasion depth at different invasion times is simulated.

10. The method according to claim 1, characterized in that In the step of establishing the comprehensive prediction model, the quantitative prediction operation model for determining the invasion depth, formation physical parameters, fluid characteristic parameters and invasion time under a fixed pressure difference is as follows: Wherein, r_invasion_unip is the invasion depth under fixed pressure difference, r_invasion_pr represents the invasion depth affected by porosity; r_invasion_pk represents the invasion depth determined by permeability; r_invasion_ps represents the invasion depth affected by water saturation; r_invasion_pv represents the invasion depth affected by formation water viscosity; the weight coefficients of porosity, permeability, saturation and fluid viscosity determined by the hierarchical analysis method are Wpor, Wpem, Wsat and Wvis respectively.

11. The method according to claim 1, characterized in that: In the step of establishing the comprehensive prediction model, based on the changing law of invasion depth with invasion time under different pressure differences, the relationship between invasion depths under different pressure differences is determined in combination with Darcy's law. The invasion depth prediction model that comprehensively considers pressure difference, invasion time, formation physical properties and fluid characteristics is determined in combination with the invasion depth relationship under different pressure differences as follows: Among them, varp and unip are different pressure differences.

12. A drilling fluid invasion prediction system based on an invasion depth calculation model, characterized in that: The system executes the method according to any one of claims 1 to 11.

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