Evaluation Method and Device for Compressibility Coefficient of Stress-Sensitive Clastic Rock Reservoirs

Abstract

The present application discloses a method and device for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir, relating to the technical field of oil and gas exploration and development. The method includes: obtaining logging data and standard cores of a target area, conducting experimental measurements on the standard cores, and combining the logging data to obtain the physical parameters of the target area; quantifying the pore structure according to the physical parameters to determine the pore structure index; determining the cement influence coefficient of the cement based on the physical parameters; constructing a dynamic compressibility coefficient model according to the pore structure index and the cement influence coefficient; and determining the compressibility coefficient of the target area through the dynamic compressibility coefficient model. It solves the problems that the process of obtaining the compressibility coefficient by the existing evaluation method of the compressibility coefficient is cumbersome and prone to deviation. It can improve the reliability of the compressibility coefficient, save experimental costs and time costs, and provide reliable data support for oil and gas development.

Description

Technical Field

[0001] This application relates to the technical field of oil and gas exploration and development, and particularly relates to a method and device for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir. Background Art

[0002] The compressibility coefficient of a rock refers to the change in pore volume per unit volume of rock when the reservoir pressure decreases by 1 MPa. It is an important parameter in material balance calculations and well test interpretations in oil and gas reservoir engineering. It is mainly applied in the following aspects: affecting the establishment and solution of the material balance equation, and thus accurately predicting the production dynamics and remaining reserves of oil and gas reservoirs; playing a key role in well test interpretation, helping interpreters accurately judge the permeability, compressibility and other characteristics of the reservoir, and providing an important basis for the development of oil and gas reservoirs; affecting the accuracy and reliability of numerical simulation models, and an accurate compressibility coefficient can improve the accuracy of numerical simulation and provide strong support for optimizing the development plan of oil and gas reservoirs; affecting the evaluation results of the elastic production capacity and dynamic geological reserves of the reservoir, and thus evaluating the exploitation potential and economic benefits of the reservoir.

[0003] At present, the method for developing the compressibility coefficient of core samples in the target formation is to detect the variation law of the compressibility coefficient by simulating different pressure and fluid conditions. The main methods include the core confining pressure porosity and permeability measuring method, the theoretical formula method, etc. Although the core confining pressure porosity and permeability measuring method can better solve the core pore and permeability parameters under the condition of simulating the true formation confining pressure, the triaxial stress that can be simulated by this method is X = Y = Z, which does not conform to the actual stress conditions, and the test fluid medium is gas. In addition, the overall test process of this method is relatively complicated, and the test cost is relatively high. Especially for low-permeability to extra-low-permeability cores, the test time is long and the accuracy is low. The theoretical formula method requires more parameters to be determined. For the convenience of calculation, many artificial assumptions are made. Therefore, it cannot reflect the true situation of actual reservoir rocks, is prone to deviation, and the calculation process is cumbersome, which is not conducive to practical production applications. Summary of the Invention

[0004] By providing a method and device for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir in the embodiments of this application, the problem that the existing method for evaluating the compressibility coefficient is cumbersome in the process of obtaining the compressibility coefficient and prone to deviation is solved.

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir, including: obtaining well logging data and standard cores of a target area, conducting experimental measurements on the standard cores, and combining the well logging data to obtain physical parameters of the target area; quantifying the pore structure according to the physical parameters to determine a pore structure index; determining a cement influence coefficient of the cement based on the physical parameters; constructing a dynamic compressibility coefficient model according to the pore structure index and the cement influence coefficient; and determining the compressibility coefficient of the target area through the dynamic compressibility coefficient model.

[0006] In combination with the first aspect, in a possible implementation manner, the physical parameters include burial depth and porosity, elastic modulus, pore medium type, and cement content corresponding to different burial depths.

[0007] In combination with the first aspect, in a possible implementation manner, the conducting experimental measurements on the standard cores and combining the well logging data to obtain physical parameters of the target area includes: constructing well logging curves based on the rock physical property data in the well logging data; where the well logging data includes rock physical property data and well logging imaging data; using the acoustic travel time well logging curve in the well logging curves to determine the elastic modulus at different depths; measuring the porosity, pore size distribution, and pore morphology of the standard cores at different burial depths through experimental measurement methods, and combining the well logging imaging data to determine the pore medium type therein; and determining the cement content at different burial depths through experimental measurement methods.

[0008] In combination with the first aspect, in a possible implementation manner, after the conducting experimental measurements on the standard cores and combining the well logging data to obtain physical parameters of the target area, it further includes: using the physical parameters, the well logging curves, and the well logging imaging data as samples to train a rock physical property model constructed based on a neural network model; and using the trained rock physical property model to output the porosity, elastic modulus, pore medium type, and cement content at different burial depths.

[0009] In combination with the first aspect, in a possible implementation manner, the quantifying the pore structure according to the physical parameters to determine a pore structure index includes: quantifying the pore structure according to the porosity, pore size distribution, and pore morphology of the standard cores as follows:

[0010] ;

[0011] In the formula, represents the i-th pore structure index, represents the weight coefficient of the i-th pore medium type, represents the porosity of the i-th pore medium type, represents the complexity of the throat j, represents the average length of the throat j, represents the average diameter of the throat j represents the coefficient of variation of the diameter of the throat j, n represents the total number of pore medium types, and m represents the total number of throats represents the porosity attenuation coefficient of the i-th pore medium type

[0012] Combined with the first aspect, in a possible implementation manner, determining the cement influence coefficient of the cement based on the physical parameters includes: determining the cement influence coefficient of the cement according to the cement content at different burial depths, as follows:

[0013] , ;

[0014] In the formula, represents the cement influence coefficient of the cement d represents the cement content of the cement d represents the strength factor of the cement d represents the burial depth of the cement d represents the temperature at the burial depth corresponding to the standard core where the cement d is located

[0015] Combined with the first aspect, in a possible implementation manner, constructing a dynamic compressibility model according to the pore structure index and the cement influence coefficient, as follows:

[0016] ;

[0017] In the formula, represents the compressibility of the target area represents the i-th pore structure index represents the porosity attenuation coefficient of the i-th pore medium type represents the pore structure coefficient represents the cement influence coefficient of the cement d represents the cement correction coefficient represents the stress sensitivity index represents the strength factor of the cement d

[0018] Combined with the first aspect, in a possible implementation manner, the calculation method of the porosity attenuation coefficient is as follows:

[0019] ;

[0020] The calculation method of the stress sensitivity index is as follows:

[0021] ;

[0022] The calculation method of the strength factor is as follows:

[0023] ; where ;

[0024] In the formula represents the porosity attenuation coefficient of the i-th pore medium type, represents the burial depth of the i-th pore medium type, represents the initial porosity, represents the stress sensitivity index, represents the relative content of cement d, represents the elastic modulus of the main mineral component of cement d, represents the temperature at the burial depth corresponding to the standard core where cement d is located, represents the complexity of throat j, represents the strength factor of cement d, represents the burial depth of cement d, represents the surface temperature.

[0025] In a second aspect, an apparatus for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir according to an embodiment of the present application includes: an acquisition module configured to acquire well logging data and standard cores of a target area, perform experimental measurements on the standard cores, and acquire physical parameters of the target area in combination with the well logging data; a quantification module configured to quantify the pore structure according to the physical parameters to determine a pore structure index; a determination module configured to determine a cement influence coefficient of the cement based on the physical parameters; a construction module configured to construct a dynamic compressibility coefficient model according to the pore structure index and the cement influence coefficient; and a compressibility coefficient determination module configured to determine the compressibility coefficient of the target area through the dynamic compressibility coefficient model.

[0026] In a third aspect, an apparatus according to an embodiment of the present application includes: a processor; a memory for storing processor-executable instructions; when the processor executes the executable instructions, the method as described in the first aspect or any one of the possible implementation manners of the first aspect is implemented.

[0027] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0028] By quantifying the pore structure, the embodiments of the present application can comprehensively consider the influence of different physical parameters on the pore structure; by determining the cement influence coefficient, the influence of burial depth on the cement content can be considered; by establishing a dynamic model of the compressibility coefficient, the subsequent process of evaluating the compressibility coefficient can be simplified. Only by obtaining the physical parameters of the target area and inputting them into the dynamic model of the compressibility coefficient can the compressibility coefficient be obtained. This effectively solves the problems that the existing evaluation methods of the compressibility coefficient are cumbersome in the process of obtaining the compressibility coefficient and prone to deviation. It can improve the reliability of the compressibility coefficient, save experimental costs and time costs, and provide reliable data support for oil and gas development. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments of the present application or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0030] Figure 1 It is a flowchart of the method for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir provided by the embodiments of the present application;

[0031] Figure 2 It is a schematic structural diagram of the device for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir provided by the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0033] The following explains some technologies related to the embodiments of the present application to facilitate understanding. It should be considered that they are merely illustrative. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described here without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, some descriptions of well-known functions and structures are omitted in the following description.

[0034] Figure 1 It is a flowchart of the method for evaluating the compressibility coefficient of a stress-sensitive clastic reservoir provided by the embodiments of the present application, including steps 101 to 105. Among them, Figure 1This is only one execution order shown in the embodiments of this application, and does not represent the only execution order of the method for evaluating the compressibility coefficient of stress-sensitive clastic rock reservoirs. Under the condition that the final result can be achieved, Figure 1 the steps shown can be executed in parallel or reversed.

[0035] Step 101: Obtain the logging data and standard cores of the target area, conduct experimental measurements on the standard cores, and combine the logging data to obtain the physical parameters of the target area. In the embodiments of this application, determine the burial depth range of the target area, use drilling equipment to drill core samples at different burial depths (samples can be taken at intervals of every 50 m, and the shallow layer can be encrypted to intervals of 20 m), and ensure the integrity and representativeness of the core samples, avoiding contamination and damage. At the same time, record the geological information of the target area, such as lithology, horizon, burial depth, etc. Lower the downhole equipment (or electrode system) equipped with sensors into the well through the cable to measure various rock physical property data. Or use technologies such as acoustic logging and density logging to obtain other rock physical property data. Then, preprocess the measured rock physical property data. Specifically, align the rock physical property data in depth so that the various rock physical property data at each depth are aligned at the same sampling point. Smooth the curves of the rock physical property data to eliminate small changes caused by non-stratigraphic reasons. Correct the environment of the rock physical property data to eliminate the influence within the detection range of the instrument, and finally perform numerical standardization to eliminate systematic errors.

[0036] In addition, those skilled in the art can also use imaging logging technology to collect formation information along the longitudinal, circumferential or radial direction of the wellbore to obtain logging imaging data (two-dimensional image of the wellbore wall or three-dimensional image within a certain detection depth around the wellbore).

[0037] Cut and polish the core samples obtained at different burial depths to prepare standard cores with a diameter of 25 mm and a height of 50 mm, and label the standard cores at different burial depths.

[0038] In the embodiments of this application, conduct experimental measurements on the standard cores and combine the logging data to obtain the physical parameters of the target area, including: constructing logging curves based on the rock physical property data in the logging data. Among them, the logging data includes rock physical property data and logging imaging data. Use the acoustic travel time logging curve in the logging curve to determine the elastic modulus at different depths. Measure the porosity, pore size distribution and pore morphology of the standard cores at different burial depths through experimental measurement methods, and combine the logging imaging data to determine the pore medium type therein. Determine the cement content at different burial depths through experimental measurement methods.

[0039] Specifically, plot the preprocessed rock physical property data as logging curves. Use the acoustic travel time logging curve in the logging curve to determine the elastic modulus at different depths, specifically as follows:

[0040] .

[0041] In the formula, represents the elastic modulus with a burial depth of i in the target area, represents the density of the rock reservoir with a burial depth of i in the target area (obtained from the density log curve in the logging curve), represents the shear wave travel time (obtained from the acoustic wave travel time log curve in the logging curve), represents the compressional wave travel time (obtained from the acoustic wave travel time log curve in the logging curve). By considering the relationship between the propagation speed of sound waves in rocks and the rock density, this method can accurately calculate the elastic modulus of the target area.

[0042] Porosity is a measure of the proportion of pore space in the rock to the total volume, and pore size distribution refers to the proportion of pores with different pore sizes in the rock. Methods such as mercury intrusion method, nitrogen adsorption method, and air pressure balance method can be used to measure the porosity and pore size distribution of standard cores at different burial depths. Pore morphology refers to the shape, size, and distribution characteristics of pores in the rock, which can be obtained by analyzing logging imaging data. In addition, those skilled in the art can also obtain porosity, pore size distribution, and pore morphology by making the standard core into a rock thin section or performing scanning electron microscope image analysis on the standard core.

[0043] Clastic rock reservoirs have diverse pore medium types, which can be mainly divided into two categories according to their origin: primary pores and secondary pores. Primary pores mainly include intergranular pores and micro-pores within matrix. Intergranular pores are the most important type of primary pores in clastic rocks, which are formed by the spaces between clastic grains. Their porosity decreases with the increase of burial depth, but the decreasing rate is relatively slow. Micro-pores within matrix refer to the tiny pores contained within the matrix (i.e., fine-grained sediments such as clay). Secondary pores refer to the pores formed in or after the diagenetic process of clastic rocks due to various geological processes (such as dissolution, compaction, cementation, etc.), and mainly include extra-large pores, mold pores, intra-component pores and fractures. According to the Schmidt standard, pores with a size exceeding 1.2 times the diameter of adjacent grains are classified as extra-large pores, and most of them are secondary pores. Mold pores refer to the pores that maintain the original fabric shape after the dissolution of shell debris, carbonate grains, and crystalline minerals (salt, gypsum, siderite) with certain characteristic geometric shapes in sandstone, and belong to the secondary pores formed by dissolution. Intra-component pores refer to the pores that appear within all components (such as grains, matrix, cement). Although fractures in sandstone are relatively minor, when strong dissolution occurs along the fractures, the fractures can also become important reservoir spaces. Fractures include tectonic fractures, diagenetic fractures, etc. In addition, there are also intra-granular dissolution pores: pores formed by the dissolution within grains; intergranular dissolution pores: pores formed by the dissolution between grains; super-grain pores: a special type of secondary pores whose size exceeds the diameter of adjacent grains; inter-crystalline pores: pores formed by the spaces between crystals, usually appearing in cement or authigenic minerals.

[0044] Based on porosity, pore size distribution, and pore morphology, this application can preliminarily determine the type of pore medium, such as intergranular pores, extra-large pores, mold pores, fractures, etc. Specifically, during the formation of sedimentary rocks, the porosity of primary pores is usually relatively high because these pores are naturally formed during grain accumulation and will maintain a certain continuity in a specific area. The pore size distribution of primary pores is usually relatively narrow, and the pore size is closely related to the grain size distribution of sediments. For example, the size of intergranular pores is usually comparable to the size of sedimentary grains. The pore size distribution of secondary pores is usually relatively wide, and the pore size is related to the intensity of later modification. For example, pores formed by dissolution may have a relatively large pore size, and the width of fractures may vary from micrometers to millimeters. The pore morphology of primary pores is usually regular. For example, intergranular pores are usually polygonal, and micro-pores within matrix are usually circular or elliptical. The pore morphology of secondary pores is usually irregular. For example, pores formed by dissolution may be irregular, and fractures may be linear or branched. In addition, those skilled in the art can also use techniques such as scanning electron microscopy, focused ion beam technology, and X-ray computed tomography to determine the type of pore medium.

[0045] In the embodiments of the present application, the core thin section method is mainly used to determine the cement content. Specifically, a standard core is prepared into a core thin section, and then microscopic images of 15-20 fields of view are obtained by observing under a polarized light microscope. Parameters such as cement type and content are extracted and statistically analyzed through image analysis software, so as to measure the cement content of standard cores at different burial depths, and further obtain the cement content at different burial depths in the target area.

[0046] The method for obtaining the cement content here is only one embodiment of the present application and does not limit the scope of protection of the application. Those skilled in the art can also use other methods to measure the cement content of standard cores at different burial depths, so as to obtain the cement content at different burial depths in the target area.

[0047] In addition, in the embodiments of the present application, physical parameters, logging curves, and logging imaging data are used as samples to train a rock physical property model constructed based on a neural network model. The trained rock physical property model is used to output porosity, elastic modulus, pore medium type, and cement content at different burial depths.

[0048] Specifically, the measured physical parameters and the corresponding logging curves and logging imaging data are used as samples to train a rock physical property model constructed based on a neural network model, and porosity, elastic modulus, pore medium type, and cement content at different burial depths are output. Exemplarily, neural network models such as multi-layer perceptron (MLP), long short-term memory network (LSTM), recurrent neural network (RNN), and their variants are used.

[0049] Step 102: Quantify the pore structure according to physical parameters to determine the pore structure index. In the embodiments of the present application, pores and throats together constitute the pore system of the reservoir. Pores serve as the storage space, and throats serve as the channels for fluid flow. If there is a lack of effective throat connection between pores, then even if the porosity is very high, the permeability of the reservoir may be very low. Moreover, the diameter, length, and complexity of the throats also have a great influence on the fluid during the flow process. If the pores are very large and the throats are very thin (small diameter), then the fluid will encounter great resistance during the flow process. On the contrary, if the sizes of the pores and throats are moderate and match each other, then the fluid flow will be smoother. The longer the throat length, the greater the pressure loss caused by friction and collision during the fluid flow process, which may affect the fluid recovery rate and development efficiency of clastic rock reservoirs. The higher the complexity of the throats, the greater the resistance to fluid flow between pores, which will reduce the connectivity between pores. If the length or complexity of the throats is relatively high, it will hinder the connectivity between pores, and it is very likely that some pores will become ineffective pores, thereby reducing the effective porosity of the reservoir.

[0050] The present application quantifies the pore structure according to the porosity, pore size distribution, and pore morphology of the standard core as follows:

[0051] .

[0052] Among them, .

[0053] In the formula, represents the i-th pore structure index, represents the weight coefficient of the i-th pore medium type, represents the porosity of the i-th pore medium type, represents the complexity of the throat j, represents the average length of the throat j, represents the average diameter of the throat j, represents the coefficient of variation of the diameter of the throat j, n represents the total number of pore medium types, and m represents the total number of throats, represents the porosity attenuation coefficient of the i-th pore medium type, represents the porosity attenuation coefficient of the i-th pore medium type, which characterizes the variation relationship of different pore medium types with burial depth, represents the burial depth of the i-th pore medium type, represents the initial porosity (measured by experiment, and the measured porosity data in this application is between 25% and 38%), and e is a mathematical constant, approximately equal to 2.71828.

[0054] Among them, the average diameter and average length of the throat can be measured according to the previous thin-section observation experiments, scanning electron microscope experiments or mercury injection tests in the laboratory, and the average values of the diameters and lengths of each throat are obtained. The complexity of the throat is based on the thin-section observation experiment. The standard core is made into a thin section, and an evaluation index system is constructed according to the key parameters such as the size, shape, distribution, permeability, and porosity of the throat observed under the microscope, and the complexity of the throat is obtained through the analytic hierarchy process weighting and the fuzzy mathematics method. In addition, those skilled in the art can also conduct physical experiments, using the flow efficiency of the fluid in the throat as the evaluation standard for the complexity of the throat. The coefficient of variation of the diameter of the throat represents the degree of dispersion of the throat diameter, which is the ratio of the standard deviation of the throat diameter to the average diameter.

[0055] Step 103: Determine the cement influence coefficient of the cement based on physical parameters. In the embodiments of the present application, as the burial depth of the clastic rock reservoir increases, the temperature and pressure gradually rise, resulting in changes in diagenesis (diagenesis includes compaction, cementation, dissolution, etc.). In the initial stage of the burial of the clastic rock reservoir, compaction is the dominant factor, which will rapidly reduce the porosity of the reservoir. As the burial depth increases, the compaction gradually weakens, and cementation begins to dominate. The reason for the weakening of compaction is the rearrangement and close contact of rock particles, as well as the reduction of pores between particles, resulting in the rock becoming harder and reducing the further compaction space.

[0056] As the burial depth increases, the cementation strengthens and the cement content gradually increases. This is because high-temperature and high-pressure conditions are conducive to the formation and precipitation of cement. The type of cement may also change with the change of burial depth. For example, in shallow reservoirs, soft cements such as mudstone and calcium-mudstone are more common, and in deep reservoirs, hard cements such as silica and calcite dominate.

[0057] As the cement content increases, the porosity and permeability of the reservoir usually decrease. This is because the cement will fill the pores and throats between particles, reducing the seepage space of the fluid. When the cement content is too high, the reservoir may become very dense, resulting in difficulty in oil and gas migration and storage. Under different burial depth conditions, due to different cementation, the reservoir type may also change. Therefore, it is necessary to comprehensively consider the influence of burial depth on the cement content.

[0058] In the embodiments of the present application, the cement influence coefficient of the cement is determined according to the cement content at different burial depths, as follows:

[0059] , .

[0060] Among them, the calculation method of the strength factor is as follows:

[0061] ; .

[0062] In the formula, represents the cement influence coefficient of cement d, represents the cement content of cement d, represents the strength factor of cement d, represents the burial depth of cement d, represents the temperature at the burial depth corresponding to the standard core where cement d is located, represents the relative content of cement d, represents the elastic modulus of the main mineral component of cement d, Represents the strength factor of cement d, Represents the burial depth of cement d, Represents the surface temperature.

[0063] Step 104: Construct a dynamic model of the compressibility coefficient based on the pore structure index and the cement influence coefficient. In the embodiment of the present application, the dynamic model of the compressibility coefficient is as follows:

[0064] 。

[0065] In the formula, Represents the compressibility coefficient of the target area, Represents the i-th pore structure index, Represents the porosity attenuation coefficient of the i-th pore medium type, which is used to characterize the attenuation change of pores of different pore medium types, Represents the pore structure coefficient, which is used to characterize the complexity and irregularity of the pore structure. Exemplarily, the pore structure coefficient of the intergranular pore - solution pore type is set to 0.8, the pore structure coefficient of the solution pore - intergranular pore type is set to 0.6, the pore structure coefficient of the intergranular pore - micropore type is set to 0.4, and the pore structure coefficient of the microfracture - fracture type is set to 0.35, Represents the cement influence coefficient of cement d, Represents the cement correction coefficient. Exemplarily, the cement correction coefficient of silica is set to 1.0, and the cement correction coefficient of calcite is set to 1.2, Represents the stress sensitivity index, Represents the strength factor of cement d.

[0066] Among them, the calculation method of the stress sensitivity index is as follows:

[0067] 。

[0068] In the formula, Represents the stress sensitivity index, Represents the complexity of the throat j.

[0069] Step 105: Determine the compressibility coefficient of the target area through the dynamic model of the compressibility coefficient. In the embodiment of the present application, according to the above dynamic model of the compressibility coefficient, by inputting the physical parameters (porosity, elastic modulus, pore medium type, and cement content) of the target area, the compressibility coefficient of the target area can be obtained.

[0070] In an embodiment of the present application, to verify the accuracy of the method proposed in the present application, cores of different pore medium types in some clastic rock reservoirs in the laboratory were selected for comparative experiments, and the results are shown in Table 1 below. Among them, the ground conditions represent the test conditions at normal temperature and pressure. The measured compressibility coefficient (Cp) is calculated based on the current national standard SY / T5815-2016 Determination Method for Rock Pore Volume Compressibility Coefficient. This method uses a test system of a high-temperature and high-pressure core holder and a high-precision measuring instrument to fully simulate the formation conditions for testing. The compressibility coefficient (Cp) evaluated by the method is the compressibility coefficient calculated by the compressibility coefficient evaluation method described in the present application.

[0071] Table 1 Comparison Table of Compressibility Coefficient (Cp) Evaluation and Measured Compressibility Coefficient (Cp) Data

[0072]

[0073] Although the present application provides method operation steps as described in the embodiments or flowcharts, based on routine or non-creative labor, there may be more or fewer operation steps. The step sequence listed in this embodiment is only one of the ways of the execution sequences of numerous steps and does not represent the only execution sequence. When the actual device or client product is executed, it can be executed in the method sequence shown in this embodiment or in parallel (for example, in an environment of parallel processors or multi-threaded processing).

[0074] As Figure 2 shown, the embodiment of the present application also provides a device 200 for evaluating the compressibility coefficient of a stress-sensitive clastic rock reservoir. The device includes: an acquisition module 201, a quantification module 202, a determination module 203, a construction module 204, and a compressibility coefficient determination module 205, which are specifically as follows.

[0075] The acquisition module 201 is used to acquire well logging data and standard cores of the target area, conduct experimental measurements on the standard cores, and obtain the physical parameters of the target area in combination with the well logging data.

[0076] The quantification module 202 is used to quantify the pore structure according to the physical parameters to determine the pore structure index.

[0077] The determination module 203 is used to determine the cement influence coefficient of the cement based on the physical parameters.

[0078] The construction module 204 is used to construct a dynamic compressibility coefficient model according to the pore structure index and the cement influence coefficient.

[0079] The compressibility coefficient determination module 205 is used to determine the compressibility coefficient of the target area through the dynamic compressibility coefficient model.

[0080] Some modules in the device described in this application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0081] The devices or modules illustrated in the above application embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. For the convenience of description, when describing the above devices, they are divided into various modules according to functions and described separately. When implementing the embodiments of this application, the functions of each module can be implemented in the same or multiple software and / or hardware. Of course, the module that implements a certain function can also be implemented by combining multiple sub-modules or sub-units.

[0082] The methods, devices or modules described in this application can be implemented in the form of computer-readable program code. The controller can be implemented in any appropriate manner. For example, the controller can take the form of, for example, a microprocessor or a processor, and a computer-readable medium storing computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, application specific integrated circuit (ASIC), programmable logic controller, and embedded microcontroller. Examples of the controller include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, the method steps can be logically programmed to enable the controller to be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, and embedded microcontrollers to achieve the same function. Therefore, such a controller can be regarded as a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or structures within the hardware component.

[0083] The embodiments of this application also provide a device, which includes: a processor; a memory for storing processor-executable instructions; when the processor executes the executable instructions, the method described in the embodiments of this application is implemented.

[0084] The embodiments of the present application further provide a non-volatile computer-readable storage medium, on which a computer program or instruction is stored. When the computer program or instruction is executed, the method described in the embodiments of the present application is implemented.

[0085] In addition, in each embodiment of the present invention, each functional module may be integrated in a processing module, or each module may exist alone, or two or more modules may be integrated in one module.

[0086] The above storage medium includes but is not limited to Random Access Memory (RAM), Read-Only Memory (ROM), Cache, Hard Disk Drive (HDD), or Memory Card. The memory may be used to store computer program instructions.

[0087] From the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary hardware. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, or can also be reflected in the implementation process of data migration. The computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which may be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments of the present application.

[0088] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. All or part of the present application can be used in many general-purpose or special-purpose computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, mobile communication terminals, multi-processor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on.

[0089] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present application.

Claims

1. A method for evaluating the compressibility of stress-sensitive clastic reservoirs, characterized in that: include: Acquire well logging data and standard cores of the target area, perform experimental measurements on the standard cores, and acquire physical parameters of the target area in combination with the well logging data; Quantifying the pore structure according to the physical parameters to determine the pore structure index includes: quantifying the pore structure according to the porosity, pore size distribution and pore morphology of the standard core, as follows: ； In the formula, represents the i-th pore structure index, represents the weight coefficient of the i-th porous medium type, represents the porosity of the i-th porous medium type, represents the complexity of throat j, represents the average length of the throat j, represents the average diameter of the throat j, represents the coefficient of variation of the diameter of throat j, n represents the total number of porous media types, m represents the total number of throats, represents the porosity attenuation coefficient of the i-th porous medium type; Determining the cementing influence coefficient of the cementing material based on the physical parameters includes: determining the cementing influence coefficient of the cementing material according to the cementing content at different burial depths, as follows: ； In the formula, represents the cementing material influence coefficient of the cementing material d, represents the cement content of cement d, represents the strength factor of the cement d; A dynamic model of compression coefficient is constructed according to the pore structure index and the cementing material influence coefficient, as follows: ； Where Cp represents the compression coefficient of the target area, represents the i-th pore structure index, represents the porosity attenuation coefficient of the i-th porous medium type, represents the pore structure coefficient, represents the cementing material influence coefficient of the cementing material d, represents the cement correction factor, represents the stress sensitivity index, represents the strength factor of the cement d; The calculation method of the porosity attenuation coefficient is as follows: ； The calculation method of the stress sensitivity index is as follows: ； The calculation method of the intensity factor is as follows: ;in, ; In the formula, represents the porosity attenuation coefficient of the i-th porous medium type, represents the buried depth of the i-th porous medium type, represents the initial porosity, represents the stress sensitivity index, Indicates the relative content of cement d, represents the elastic modulus of the main mineral component of the cement d, Indicates the temperature at the burial depth of the standard core where the cement d is located. represents the complexity of throat j, represents the strength factor of the cement d, represents the buried depth of cement d, represents the surface temperature; The compression coefficient of the target area is determined by the compression coefficient dynamic model.

2. The method according to claim 1, characterized in that The physical parameters include burial depth and porosity, elastic modulus, porous medium type and cement content corresponding to different burial depths.

3. The method according to claim 2, characterized in that The experimental measurement of the standard core and the acquisition of the physical parameters of the target area in combination with the logging data include: Constructing a logging curve based on the rock property data in the logging data; wherein the logging data includes the rock property data and the logging imaging data; Determining elastic moduli at different depths using the acoustic time difference logging curve in the logging curve; The porosity, pore size distribution and pore morphology of standard cores at different burial depths are measured by experimental determination methods, and the porous medium type therein is determined in combination with the logging imaging data; The cement content at different burial depths is determined by experimental measurement methods.

4. The method according to claim 3, characterized in that After the standard core is experimentally measured and the physical parameters of the target area are obtained in combination with the logging data, the method further includes: Using the physical parameters, the logging curves and the logging imaging data as samples, training a rock property model constructed based on a neural network model; The trained rock physical property model is used to output the porosity, elastic modulus, porous medium type and cement content at different burial depths.

5. A compressibility evaluation device for stress-sensitive clastic reservoirs implementing the method according to any one of claims 1 to 4, characterized in that: include: An acquisition module is used to acquire well logging data and standard cores of a target area, perform experimental measurements on the standard cores, and acquire physical parameters of the target area in combination with the well logging data; The quantification module is used to quantify the pore structure according to the physical parameters to determine the pore structure index, including: quantifying the pore structure according to the porosity, pore size distribution and pore morphology of the standard core, as follows: ； In the formula, represents the i-th pore structure index, represents the weight coefficient of the i-th porous medium type, represents the porosity of the i-th porous medium type, represents the complexity of throat j, represents the average length of the throat j, represents the average diameter of the throat j, represents the coefficient of variation of the diameter of throat j, n represents the total number of porous media types, m represents the total number of throats, represents the porosity attenuation coefficient of the i-th porous medium type; The determination module is used to determine the cement influence coefficient of the cement based on the physical parameters, including: determining the cement influence coefficient of the cement according to the cement content at different burial depths, as follows: ； In the formula, represents the cementing material influence coefficient of the cementing material d, represents the cement content of cement d, represents the strength factor of the cement d; A construction module is used to construct a dynamic model of compression coefficient according to the pore structure index and the cementing material influence coefficient, as follows: ； Where Cp represents the compression coefficient of the target area, represents the i-th pore structure index, represents the porosity attenuation coefficient of the i-th porous medium type, represents the pore structure coefficient, represents the cementing material influence coefficient of the cementing material d, represents the cement correction factor, represents the stress sensitivity index, represents the strength factor of the cement d; The calculation method of the porosity attenuation coefficient is as follows: ； The calculation method of the stress sensitivity index is as follows: ； The calculation method of the intensity factor is as follows: ;in, ; In the formula, represents the porosity attenuation coefficient of the i-th porous medium type, represents the buried depth of the i-th porous medium type, represents the initial porosity, represents the stress sensitivity index, Indicates the relative content of cement d, represents the elastic modulus of the main mineral component of the cement d, Indicates the temperature at the burial depth of the standard core where the cement d is located. represents the complexity of throat j, represents the strength factor of the cement d, represents the buried depth of cement d, represents the surface temperature; The compression coefficient determination module is used to determine the compression coefficient of the target area through the compression coefficient dynamic model.

6. A device for performing a method for evaluating the compressibility of a stress-sensitive clastic reservoir, characterized in that: include: processor; a memory for storing processor-executable instructions; When the processor executes the executable instructions, the method according to any one of claims 1 to 4 is implemented.

Images