Marine facies sandstone interlayer distribution scale prediction method and device based on dynamic data, medium and equipment

Abstract

The invention relates to a marine facies sandstone interlayer distribution scale prediction method and device based on dynamic data, a medium and equipment. The method comprises the following steps: acquiring actually measured pressure drop and pressure recovery data of a marine facies sandstone interlayer; and calculating an instantaneous formation coefficient # imgabs0 # according to the instantaneous formation coefficient # imgabs1 # during pressure drop, calculating a formation coefficient # imgabs4 # according to # imgabs3 # during pressure drop, so as to obtain # imgabs5 # corresponding to the detection radius rn at the tn moment. The method is based on the pressure drop or pressure recovery data of a single well, and a distribution function of the permeability changing along with the radial distance is deduced; by solving 0-order and 1-order disturbance solutions in the Laplace space, the space thickness and the front edge of the interlayer at different time intervals are detected, and the space position and the distribution scale of the interlayer are quantitatively described.

Description

Technical Field

[0001] The invention relates to a method, a device, a medium and equipment for predicting the distribution scale of marine sandstone interlayers based on dynamic data, and belongs to the technical field of oil and gas field development. Background Art

[0002] The proven geological reserves of marine sandstone oilfields are large, about 1 billion cubic meters, of which bottom water heavy oil reservoirs account for a large share, about 60%. The characteristics of marine sandstone reservoirs are the widespread distribution of mud and calcareous interlayers, and the development characteristics are high liquid production. The existence of interlayers leads to the complex distribution of water flooding in the reservoir and the remaining oil, which brings great difficulties to the optimization of well location adjustment and plan formulation. Therefore, the detailed description of the spatial position and distribution scale of interlayers is an important direction for adjustment and potential tapping in the later stage of development.

[0003] Through investigation, it is found that fine logging comparison and 3D seismic technology can achieve qualitative characterization of the distribution position and scale of interlayers in wells and planes, while quantitative characterization of interlayer distribution between wells is mainly achieved through static data analysis or geological modeling. In the absence of good field outcrops or variable sedimentary environments, the quantitative relationship effect needs to be improved urgently and has the characteristics of multiple uncertainties. Therefore, how to further achieve quantitative characterization of the distribution scale, boundaries and physical properties of interlayers between wells by introducing production dynamic data is the key direction to further improve the recovery rate in the "double ultra-high" development stage of marine sandstone oilfields. Summary of the invention

[0004] In view of the above technical problems, the present invention provides a method, device, medium and equipment for predicting the distribution scale of marine sandstone interlayers based on dynamic data. The method derives the distribution function of permeability changing with radial distance based on the pressure drop or pressure recovery data of a single well, and detects the spatial thickness and front edge of the interlayers at different times by solving the 0th and 1st order perturbation solutions in the Laplace space, so as to quantitatively characterize the spatial position and distribution scale of the interlayers.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for predicting the distribution scale of marine sandstone interlayers based on dynamic data, comprising:

[0007] Obtain the measured pressure drop and pressure recovery data of marine sandstone interlayers;

[0008] Calculate the instantaneous formation coefficient using the measured pressure drop or pressure recovery data

[0009] According to the instantaneous formation coefficient Calculate the pressure drop

[0010] According to the pressure drop Calculate the formation factor To get t n Time detection radius r n Corresponding

[0011] The method for predicting the distribution scale of marine sandstone interlayers is preferably based on the following assumptions:

[0012] Permeability is a function of the spatial parameters r and θ (angle), single-phase fluid is slightly compressible, constant rock and fluid properties, top and bottom are closed, infinite oil reservoirs of equal thickness, and fluid flows at a constant velocity.

[0013] The method for predicting the distribution scale of marine sandstone interlayers is preferably based on the instantaneous formation coefficient The calculation formula is as follows:

[0014]

[0015] Where k is the permeability, mD; h is the effective thickness, m; μ is the viscosity, mPa·s; q is the flow rate, m 3 / d; B is the volume coefficient, dimensionless; Δp w is the pressure drop, MPa.

[0016] The method for predicting the distribution scale of marine sandstone interlayers is preferably based on the pressure drop. The calculation formula is as follows:

[0017]

[0018] in,

[0019]

[0020] Where k is the permeability, mD; h is n is the effective thickness of the nth layer, m; μ is the viscosity, mPa·s; r w , wellbore radius, m; B, is the volume coefficient, dimensionless; C t , comprehensive compression coefficient; t, time; r D , detection radius, m. n is the number of layers.

[0021] The method for predicting the distribution scale of marine sandstone interlayers is preferably characterized by a formation coefficient The calculation formula is as follows:

[0022]

[0023] The second aspect of the present invention provides a device for predicting the distribution scale of marine sandstone interlayers based on dynamic data, comprising:

[0024] The first processing unit is used to obtain measured pressure drop and pressure recovery data of marine sandstone interlayers;

[0025] The second processing unit is used to calculate the instantaneous formation coefficient using the measured pressure drop or pressure recovery data.

[0026] The third processing unit is used to calculate the instantaneous formation coefficient Calculate the pressure drop type;

[0027] The fourth processing unit is used to Calculate the formation factor To get t n Time detection radius r n Corresponding

[0028] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the above-mentioned methods for predicting the distribution scale of marine sandstone interlayers based on dynamic data.

[0029] A fourth aspect of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned methods for predicting the distribution scale of marine sandstone interlayers based on dynamic data are implemented.

[0030] The present invention adopts the above technical solution, which has the following advantages:

[0031] The present invention introduces dynamic data, integrates pressure drop and pressure recovery data, and derives a recursive inversion algorithm based on the traditional Oliver approximate solution to establish a pressure derivative solution suitable for arbitrary changes in permeability and a reduced-order calculation method. By calculating the permeability at any position in space, the spatial position, distribution scale and physical properties of the well interval interlayer are quantitatively characterized. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A single well pressure data processing diagram provided by an embodiment of the present invention;

[0033] Figure 2 This is a boundary detection map of the interlayer distribution scale provided in this embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention is described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work are within the scope of protection of the present invention.

[0035] Unless otherwise defined, the technical or scientific terms used in the present invention shall have the usual meanings understood by persons with ordinary skills in the field to which the present invention belongs. The words "first", "second", "third", "fourth" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Words such as "include" or "comprise" and the like mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect" or "connected" and the like are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.

[0036] For ease of description, spatially relative terms may be used herein to describe the relationship of one element or feature relative to another element or feature as shown in the figures, such as "inside", "outside", "inner side", "outer side", "below", "above", etc. Such spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation depicted in the figures.

[0037] Well logging fine comparison and 3D seismic technology can achieve qualitative characterization of the distribution position and scale of interlayers in wells and planes, while quantitative characterization of interlayer distribution between wells is mainly achieved through static data analysis or geological modeling. In the absence of good field outcrops or variable sedimentary environments, the quantitative relationship effect needs to be improved urgently and has the characteristics of multiple uncertainties. Therefore, how to further achieve quantitative characterization of the distribution scale, boundaries and physical properties of interlayers between wells by introducing production dynamic data is the key direction to further improve the recovery rate in the "double ultra-high" development stage of marine sandstone oilfields.

[0038] In view of the above technical problems, the present invention provides a method, device, medium and equipment for predicting the distribution scale of marine sandstone interlayers based on dynamic data. The method derives the distribution function of permeability changing with radial distance based on the pressure drop or pressure recovery data of a single well, and detects the spatial thickness and front edge of the interlayers at different times by solving the 0th and 1st order perturbation solutions in the Laplace space, so as to quantitatively characterize the spatial position and distribution scale of the interlayers.

[0039] like Figure 1 , 2As shown, the method for predicting the distribution scale of marine sandstone interlayers based on dynamic data provided by the present invention includes the following specific steps:

[0040] The present invention is based on the following basic assumptions: permeability is a function of spatial parameters r (radius) and θ (angle), single-phase fluid is slightly compressible, rock and fluid properties are constant, top and bottom are closed, and the thickness of the infinite reservoir is equal, and the fluid flows at a constant speed.

[0041] The present invention establishes a pressure derivative solution applicable to any change in permeability, which is called a general pressure derivative analytical solution. The specific steps are as follows:

[0042] Define k(r) as the harmonic mean of k(r, θ) at position r:

[0043]

[0044] Where k is the permeability, mD; h is the effective thickness, m; μ is the viscosity, mPa·s.

[0045] The dimensionless variable is defined as:

[0046]

[0047] The approximate solution can be expressed as:

[0048]

[0049] The kernel function after deformation:

[0050]

[0051] Assumptions When , that is, under homogeneous reservoir conditions, we can obtain:

[0052]

[0053] Assumptions For a homogeneous reservoir with a constant permeability k1, equation (1-8) becomes:

[0054]

[0055] From equations (1-6) and (1-9), we can derive:

[0056]

[0057] For the convenience of the following derivation, let K1 * (r D , t D )=2K * (r D , t D ),but:

[0058]

[0059] Substituting equation (1-11) into equation (1-6), we get:

[0060]

[0061] The dimensionless pressure derivative can be expressed as:

[0062]

[0063] Combining equations (1-8), (1-12) and (1-13), we obtain:

[0064]

[0065] It can be seen from formula (1-14) that the reference permeability is only implicit in the dimensionless time. Combining the characteristics of formula (1-14), the reference formation coefficient is redefined as

[0066]

[0067] because is related to the pressure derivative at a particular time, called is the instantaneous formation coefficient.

[0068] From equations (1-14) and (1-15), we can deduce:

[0069]

[0070] Define dimensionless pseudo-time:

[0071]

[0072] Then equation (1-16) becomes:

[0073]

[0074] Equation (1-19) is the general pressure derivative analytical solution (GPDS), and its mathematical expression is a first-order integral equation. This method for calculating the formation coefficient distribution of heterogeneous reservoirs is not only applicable to pressure drop situations, but also to pressure recovery situations.

[0075] In order to The permeability k(r) is obtained from the equation, assuming that k(r) can be expressed as a discrete piecewise function, that is, when r i-1 <r≤r i (i=1, 2,...,n), k(r)=k iThus, the essence of this inversion algorithm is to solve n Time detection radius r n The corresponding Detection radius r n Defined as:

[0076]

[0077] definition:

[0078]

[0079]

[0080] At t = t n At this moment, equation (1-19) is transformed into:

[0081]

[0082] From formula (1-6), we can get:

[0083]

[0084] Therefore, equation (1-24) can be rewritten as:

[0085]

[0086] From formula (1-20), we can get:

[0087]

[0088] Substituting equation (1-26) into equation (1-25), we obtain:

[0089]

[0090] We can first find:

[0091]

[0092] In formula (1-28), t1 represents the first time point at which a reliable pressure derivative value exists. Then, using formula (1-27), we can obtain Formula (5-27) can be transformed into:

[0093]

[0094] because:

[0095]

[0096] The integral in formula (1-29) can be expressed as:

[0097]

[0098] According to the definition of dimensionless Boltzmann variables, the corresponding instantaneous dimensionless Boltzmann variables are defined as:

[0099]

[0100] From formula (1-31), we get:

[0101]

[0102] Substituting equation (1-32) into equation (1-30), we obtain:

[0103]

[0104] In the area Kernel function K * (r D ,t D )≈0. Here the following dimensionless detection inner radius is defined:

[0105]

[0106] The corresponding outer detection radius is:

[0107]

[0108] For any function F(r D ), there is the following relationship:

[0109]

[0110] Combining the analysis of equations (1-30) to (1-35), equation (1-29) can be further expressed as:

[0111]

[0112] If:

[0113]

[0114] Then formula (1-36) can be simplified as:

[0115]

[0116] According to the definition of formula (1-21), the expression for calculating the formation coefficient distribution is:

[0117]

[0118] The technical solution of the present invention is described in detail below with reference to specific examples.

[0119] like Figure 1 , 2 As shown, Well B12H is located in an offshore oil field. The first well drilling operation started in 2012. The porosity of the BO16.80 layer of the well is 0.277, the permeability is 5770.8, and the water saturation is 16.6%. Combining the double logarithmic pressure curve with the interlayer detection curve near Well B12H, it can be seen that the well found interlayers when detecting at 100m.

[0120] The present invention introduces dynamic data, integrates pressure drop and pressure recovery data, and derives a recursive inversion algorithm based on the traditional Oliver approximate solution to establish a pressure derivative solution suitable for arbitrary changes in permeability and a reduced-order calculation method. By calculating the permeability at any position in space, the spatial position, distribution scale and physical properties of the well interval interlayer are quantitatively characterized.

[0121] The second aspect of the present invention provides a device for predicting the distribution scale of marine sandstone interlayers based on dynamic data, comprising:

[0122] The first processing unit is used to obtain measured pressure drop and pressure recovery data of marine sandstone interlayers;

[0123] The second processing unit is used to calculate the instantaneous formation coefficient using the measured pressure drop or pressure recovery data.

[0124] The third processing unit is used to calculate the instantaneous formation coefficient Calculate the pressure drop type;

[0125] The fourth processing unit is used to Calculate the formation factor To get t n Time detection radius r n Corresponding

[0126] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the above-mentioned methods for predicting the distribution scale of marine sandstone interlayers based on dynamic data.

[0127] A fourth aspect of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned methods for predicting the distribution scale of marine sandstone interlayers based on dynamic data are implemented.

[0128] The present invention is described in terms of flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to specific embodiments. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0129] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0130] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting the distribution scale of marine sandstone interlayers based on dynamic data, characterized in that: include: Obtain the measured pressure drop and pressure recovery data of marine sandstone interlayers; Calculate the instantaneous formation coefficient using the measured pressure drop or pressure recovery data According to the instantaneous formation coefficient Calculate the pressure drop According to the pressure drop Calculate the formation factor To get t n Time detection radius r n Corresponding 2. The method for predicting the distribution scale of marine sandstone interlayers according to claim 1, characterized in that: The method for predicting the distribution scale of marine sandstone interlayers is based on the following assumptions: Permeability is a function of the spatial parameters r and θ (angle), single-phase fluid is slightly compressible, constant rock and fluid properties, top and bottom are closed, infinite oil reservoirs of equal thickness, and fluid flows at a constant velocity.

3. The method for predicting the distribution scale of marine sandstone interlayers according to claim 1, characterized in that: Instantaneous formation coefficient The calculation formula is as follows: Where k is permeability; h is effective thickness; μ is viscosity; q is flow rate; B is volume coefficient; Δp w For pressure drop.

4. The method for predicting the distribution scale of marine sandstone interlayers according to claim 1, characterized in that: When the pressure drops The calculation formula is as follows: Where n is the number of layers.

5. The method for predicting the distribution scale of marine sandstone interlayers according to claim 1, characterized in that: Formation coefficient The calculation formula is as follows:

6. A device for predicting the distribution scale of marine sandstone interlayers based on dynamic data, characterized in that: include: The first processing unit is used to obtain measured pressure drop and pressure recovery data of marine sandstone interlayers; The second processing unit is used to calculate the instantaneous formation coefficient using the measured pressure drop or pressure recovery data. The third processing unit is used to calculate the instantaneous formation coefficient Calculate the pressure drop type; The fourth processing unit is used to Calculate the formation factor To get t n Time detection radius r n Corresponding 7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for predicting the distribution scale of marine sandstone interlayers based on dynamic data as described in any one of claims 1 to 5 are implemented.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for predicting the distribution scale of marine sandstone interlayers based on dynamic data as described in any one of claims 1 to 5 are implemented.

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