Method and system for depicting water invasion dominant channel space of fractured-porous gas reservoir

Abstract

The invention belongs to the technical field of gas reservoir exploration, and particularly relates to a method and a system for depicting a water invasion dominant channel space of a fractured-porous gas reservoir. The method comprises the following steps: establishing a dual-medium fine geological model, wherein the dual-medium fine geological model comprises a matrix porosity model and a discrete fracture network model; obtaining a matrix permeability model according to the matrix porosity model, and obtaining a fracture permeability model according to the discrete fracture network model; matrix heterogeneity characterization parameter gridding is carried out based on the matrix permeability model, and fracture heterogeneity characterization parameter gridding is carried out based on the fracture permeability model. According to the method, the near-wellbore zone water invasion channel or the seepage barrier can be accurately judged, the whole gas reservoir water invasion channel or the area to be subjected to water invasion can be predicted, the influence of human factors is reduced, and the method is visual, fine, high in calculation efficiency and high in accuracy for the crack-pore type reservoir. And predicting the geometrical morphology and spatial configuration relation of the water invasion channel with comprehensive evaluation parameters.

Description

Technical Field

[0001] This disclosure belongs to the field of gas reservoir exploration technology, and specifically relates to a method and system for spatial characterization of water intrusion dominant channels in fracture-pore gas reservoirs. Background Technology

[0002] The biggest challenge in developing water-bearing gas reservoirs is well flooding. Well flooding not only increases surface water treatment costs but also shortens the reservoir's stable production time, accelerates production decline, and reduces recovery rates, resulting in significant resource waste and economic losses. Intuitive and precise methods for predicting water intrusion channels in gas reservoirs enable technicians to take timely and accurate targeted waterproofing and water control measures, playing a crucial role in the long-term stable production and efficient development of gas reservoirs.

[0003] Currently, the commonly used methods for identifying water intrusion channels in gas reservoirs include: tracer method, well logging data identification method, well test data identification method, hierarchical analysis method, and geological modeling method. Each of these methods has its own technical limitations.

[0004] The tracer method is an engineering approach that monitors inter-well connectivity by injecting a gaseous tracer into the gas well. Its advantage is that it can provide a qualitative understanding of inter-well connectivity, but it cannot describe the details of reservoir connectivity between wells or in distant well zones.

[0005] Well logging data identification is a method that uses comprehensive interpretation of well logging curves to obtain reservoir physical parameters for a single well, thereby determining the connectivity between wells. This method can quantitatively describe the permeability changes in different sections of the well and can provide a relatively detailed description of water intrusion channels between two wells with small well spacing. However, it cannot identify connectivity in areas without well control.

[0006] Well test data identification is a method that interprets reservoir characteristic parameters using formation pressure data obtained through methods such as pressure recovery well tests and interference well tests, and determines whether there are dominant water intrusion channels or seepage barriers between wells. This method can accurately describe reservoir changes within the well-controlled area, but it cannot make judgments about areas without well control.

[0007] The Analytic Hierarchy Process (AHP) decomposes the factors involved in water intrusion channel identification into several levels according to different attributes by establishing a hierarchical structure model. The final decision result is obtained through processes such as pairwise comparison matrices and consistency checks. The advantages of this method are its simplicity and speed, but it is greatly influenced by human factors and can only be used as an auxiliary method for qualitative description.

[0008] Conventional geological modeling methods comprehensively utilize dynamic and static data of gas reservoirs to establish three-dimensional geological models, using permeability distribution as a criterion to describe the planar distribution and spatial configuration of water intrusion channels. While this method can achieve a certain degree of intuitive and detailed characterization of dominant water intrusion channels, it typically focuses on single-medium reservoirs and relies solely on permeability levels. Therefore, it fails to achieve the goal of detailed characterization and comprehensive evaluation parameters for dominant water intrusion channels in fracture-pore reservoirs. Summary of the Invention

[0009] To address the aforementioned problems, this disclosure provides a method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs, characterized in that the method includes:

[0010] A fine geological model with dual media is established, which includes a matrix porosity model and a discrete fracture network model.

[0011] The matrix permeability model is obtained based on the matrix porosity model, and the fracture permeability model is obtained based on the discrete fracture network model.

[0012] Mesh generation of matrix heterogeneity characterization parameters based on matrix permeability model, and mesh generation of fracture heterogeneity characterization parameters based on fracture permeability model;

[0013] Evaluation criteria for geological feature parameters of matrix water intrusion channels were constructed by gridding matrix heterogeneity characterization parameters, and evaluation criteria for geological feature parameters of fracture water intrusion channels were constructed by gridding fracture heterogeneity characterization parameters.

[0014] The average probability attribute body of the matrix is ​​obtained based on the evaluation criteria of geological characteristic parameters of the matrix water intrusion channel, and the average probability attribute body of the fracture is obtained based on the evaluation criteria of geological characteristic parameters of the fracture water intrusion channel.

[0015] The water intrusion channel distribution model is obtained based on the average probability attribute volume of the matrix and the average probability attribute volume of the cracks. The dominant water intrusion channels in the test area are then spatially characterized using the water intrusion channel distribution model to obtain the spatial characterization results.

[0016] Furthermore, based on the matrix porosity model, a matrix permeability model is obtained, including:

[0017] Obtain the actual values ​​of porosity and permeability of different sedimentary microphases in each sublayer;

[0018] A cross-plot is obtained by using the actual values ​​of porosity and permeability, and the cross-plot includes a curve showing the relationship between porosity and permeability;

[0019] By fitting the porosity-permeability curve, a power function with respect to porosity is obtained;

[0020] The predicted permeability values ​​under different sedimentary microfacies in each sublayer were obtained using power functions;

[0021] A matrix permeability model is derived based on the predicted permeability value.

[0022] Furthermore, based on the discrete fracture network model, a fracture permeability model is obtained, including:

[0023] Obtain the crack permeability;

[0024] The Oda method was used to obtain a fracture permeability model.

[0025] Furthermore, after meshing the matrix heterogeneity characterization parameters based on the matrix permeability model and the fracture heterogeneity characterization parameters based on the fracture permeability model, the following steps are taken:

[0026] Dimensionless transformation of characteristic parameters of matrix and crack;

[0027] The characteristic parameters include at least heterogeneity characterization parameters and permeability.

[0028] Furthermore, the evaluation criteria for the geological characteristic parameters of the water intrusion channel include: homogeneous, heterogeneous, and strongly heterogeneous.

[0029] Furthermore, based on the evaluation criteria for geological characteristic parameters of the matrix water intrusion channels, the average probability attribute body of the matrix is ​​obtained, including:

[0030] Core test permeability was used to correct discretized permeability logging curves of a single well.

[0031] Verify the correlation coefficients between the discretized permeability logging curves of a single well and various heterogeneous parameters of the matrix;

[0032] The weights of various geological characteristic parameters related to the matrix are set according to the correlation coefficient;

[0033] The average probability attribute volume of the matrix is ​​obtained by using the weights of various geological characteristic parameters and permeability of the matrix.

[0034] Furthermore, based on the evaluation criteria for geological characteristic parameters of fracture water intrusion channels, the average probability attribute body of the fracture is obtained, including:

[0035] Core test permeability was used to correct the discretized fracture strength curve of a single well;

[0036] Verify the correlation coefficients between the discretized fracture intensity curves of a single well and various heterogeneous parameters of the fracture;

[0037] The weights of various geological characteristic parameters related to cracks are set according to the correlation coefficient;

[0038] The average probability attribute body of the crack is obtained by using the weights of the geological characteristic parameters of the crack and the permeability.

[0039] Furthermore, based on the average probability attribute volume of the matrix and the average probability attribute volume of the fractures, a water intrusion channel distribution model is obtained, including:

[0040] The water intrusion channel distribution model is obtained based on the average probability attribute volume of the matrix, the average probability attribute volume of the crack, the weights of the geological characteristic parameters of the matrix, and the weights of the geological characteristic parameters of the crack.

[0041] This disclosure also proposes a spatial characterization system for water-intrusion-dominant channels in fracture-pore gas reservoirs, characterized in that the system comprises:

[0042] A module is established to build a fine geological model of dual media, which includes a matrix porosity model and a discrete fracture network model.

[0043] The first acquisition module is used to obtain the matrix permeability model based on the matrix porosity model and the fracture permeability model based on the discrete fracture network model.

[0044] The meshing module is used for meshing matrix heterogeneity characterization parameters based on the matrix permeability model and for meshing fracture heterogeneity characterization parameters based on the fracture permeability model.

[0045] The evaluation criteria module is used to construct evaluation criteria for geological feature parameters of matrix water intrusion channels by gridding matrix heterogeneity characterization parameters, and to construct evaluation criteria for geological feature parameters of fracture water intrusion channels by gridding fracture heterogeneity characterization parameters.

[0046] The second acquisition module is used to obtain the matrix average probability attribute body based on the evaluation standard of geological characteristic parameters of matrix water intrusion channel, and to obtain the fracture average probability attribute body based on the evaluation standard of geological characteristic parameters of fracture water intrusion channel.

[0047] The characterization module is used to obtain a water intrusion channel distribution model based on the average probability attribute volume of the matrix and the average probability attribute volume of the crack, and to spatially characterize the dominant water intrusion channels in the test area using the water intrusion channel distribution model to obtain spatial characterization results.

[0048] Furthermore, the system also includes:

[0049] The conversion module is used to perform dimensionless conversion of the characteristic parameters of the matrix and cracks;

[0050] The characteristic parameters include at least heterogeneity characterization parameters and permeability.

[0051] Furthermore, the second acquisition module is used to obtain the matrix average probability attribute body based on the evaluation criteria of geological characteristic parameters of matrix water intrusion channels, including:

[0052] The second acquisition module is used to correct the discretized permeability logging curves of a single well using core test permeability.

[0053] Verify the correlation coefficients between the discretized permeability logging curves of a single well and various heterogeneous parameters of the matrix;

[0054] The weights of various geological characteristic parameters related to the matrix are set according to the correlation coefficient;

[0055] The average probability attribute volume of the matrix is ​​obtained by using the weights of various geological characteristic parameters and permeability of the matrix.

[0056] Furthermore, the second acquisition module is used to obtain the average probability attribute body of the fracture based on the evaluation criteria of geological characteristic parameters of the fracture water intrusion channel, including:

[0057] The second acquisition module is used to correct the discrete fracture strength curve of a single well using the permeability of core experiments.

[0058] Verify the correlation coefficients between the discretized fracture intensity curves of a single well and various heterogeneous parameters of the fracture;

[0059] The weights of various geological characteristic parameters related to cracks are set according to the correlation coefficient;

[0060] The average probability attribute body of the crack is obtained by using the weights of the geological characteristic parameters of the crack and the permeability.

[0061] Furthermore, the characterization module, used to obtain a water intrusion channel distribution model based on the matrix average probability attribute volume and the crack average probability attribute volume, includes:

[0062] The characterization module is used to obtain the water intrusion channel distribution model based on the matrix average probability attribute volume, the crack average probability attribute volume, the weights of various geological characteristic parameters related to the matrix, and the weights of various geological characteristic parameters related to the crack.

[0063] This disclosure has the following beneficial effects:

[0064] (1) This disclosure improves the shortcomings of conventional water intrusion channel identification methods. It can not only accurately determine near-wellbore water intrusion channels or seepage barriers, but also predict water intrusion channels or areas that will be intruded into the whole gas reservoir. It also reduces the influence of human factors and realizes intuitive, detailed, computationally efficient, and comprehensive prediction of the geometric shape and spatial configuration of water intrusion channels for fracture-pore type reservoirs.

[0065] (2) This disclosure uses well seismic interpretation data and dynamic data to establish a dual-medium fine geological model, which makes the spatial characterization of water intrusion channels in fracture-pore gas reservoirs more targeted and reliable; and adopts the pore-permeability relationship formula of layered segments and phase zones when establishing the matrix permeability model, which further improves the model's precision; and obtains the fracture permeability model by Oda method.

[0066] (3) This invention achieves the goal of comprehensively evaluating parameters and intuitively and precisely predicting the geometric morphology and spatial configuration of water intrusion channels by performing gridded calculations on the heterogeneity characterization parameters of the matrix and cracks respectively, establishing the average probability volume of the matrix and cracks respectively by weighted averaging, and then integrating them into the distribution model of the maximum probability water intrusion dominant channel.

[0067] (4) This disclosure has established a process for spatial characterization of water intrusion dominant channels in fracture-pore gas reservoirs and compiled corresponding work guidelines. This process can be used for spatial characterization of water intrusion dominant channels in similar gas reservoirs. It has high practical value and broad application prospects for waterproofing, water control, ensuring stable gas reservoir production, and improving gas reservoir recovery rate.

[0068] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures pointed out in the description and the accompanying drawings. Attached Figure Description

[0069] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0070] Figure 1 A diagram illustrating the spatial characterization method of water intrusion dominant channels in fracture-pore gas reservoirs according to an embodiment of this disclosure is shown.

[0071] Figure 2 A detailed flowchart of the method for spatial characterization of water intrusion dominant channels in fracture-pore gas reservoirs in this disclosure is shown.

[0072] Figure 3 This diagram illustrates the cross-sectional view of porosity and permeability of different depositional microphases in each sublayer in the embodiments of this disclosure.

[0073] Figure 4 This diagram illustrates a matrix permeability model in an embodiment of the present disclosure.

[0074] Figure 5 This diagram illustrates a crack permeability model in an embodiment of the present disclosure.

[0075] Figure 6 This diagram illustrates the model of the permeability difference between the matrix and the crack, the permeability surge coefficient, and the permeability variation coefficient in an embodiment of this disclosure.

[0076] Figure 7 This diagram illustrates a model of the water intrusion channel distribution with average matrix probability in an embodiment of this disclosure.

[0077] Figure 8 This diagram illustrates a water intrusion channel distribution model based on the average probability of cracks in an embodiment of this disclosure.

[0078] Figure 9 This diagram illustrates a water intrusion channel model for a fracture-pore type water-bearing gas reservoir according to an embodiment of this disclosure.

[0079] Figure 10 A spatial characterization system diagram of the water intrusion dominant channels in a fracture-pore gas reservoir is shown in an embodiment of this disclosure. Detailed Implementation

[0080] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this disclosure more comprehensive and complete, and to fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more of the specific details omitted, or other methods, components, apparatus, steps, etc., can be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0081] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware units or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0082] The flowchart shown in the attached diagram is merely an illustrative example and does not necessarily include all steps. For example, some steps may be broken down, while others may be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0083] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein.

[0084] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or device that includes a series of steps or sub-modules is not necessarily limited to those steps or sub-modules that are explicitly listed, but may include other steps or sub-modules that are not explicitly listed or that are inherent to such process, method, product, or device.

[0085] like Figure 1 As shown, this disclosure proposes a method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs, the method comprising:

[0086] A fine geological model with dual media is established, which includes a matrix porosity model and a discrete fracture network model.

[0087] The matrix permeability model is obtained based on the matrix porosity model, and the fracture permeability model is obtained based on the discrete fracture network model.

[0088] Mesh generation of matrix heterogeneity characterization parameters based on matrix permeability model, and mesh generation of fracture heterogeneity characterization parameters based on fracture permeability model;

[0089] Evaluation criteria for geological feature parameters of matrix water intrusion channels were constructed by gridding matrix heterogeneity characterization parameters, and evaluation criteria for geological feature parameters of fracture water intrusion channels were constructed by gridding fracture heterogeneity characterization parameters.

[0090] The average probability attribute body of the matrix is ​​obtained based on the evaluation criteria of geological characteristic parameters of the matrix water intrusion channel, and the average probability attribute body of the fracture is obtained based on the evaluation criteria of geological characteristic parameters of the fracture water intrusion channel.

[0091] The water intrusion channel distribution model is obtained based on the average probability attribute volume of the matrix and the average probability attribute volume of the cracks. The dominant water intrusion channels in the test area are then spatially characterized using the water intrusion channel distribution model to obtain the spatial characterization results.

[0092] A certain carbonate gas reservoir is located in Central Asia. Its sedimentary characteristics are reef-shoal deposits, its structural characteristics are fault-antic structures, and its reservoir type is fracture-pore type. The internal connectivity of the gas reservoir is complex. Analysis of formation pressure, production capacity, and water production shows significant differences between wells. Conventional methods are insufficient to accurately describe the heterogeneous characteristics of the reservoir and characterize the dominant channels of water intrusion.

[0093] like Figure 2 As shown, in order to solve the above technical problems, the specific implementation of this method includes the following steps:

[0094] Step 1: Combine well seismic interpretation data and dynamic data to establish a fine geological model with dual media;

[0095] Step 2: Calculate the matrix permeability model using the porosity-permeability relationship formula of layered and microphase, and calculate the fracture permeability model using the Oda method.

[0096] Step 3: Perform gridded calculations on the heterogeneity characterization parameters of the matrix and fractures (mainly: permeability surge coefficient, permeability range, and permeability variation coefficient);

[0097] Step 4: Perform dimensionless transformation on the geological characteristic parameters of the water intrusion channel (mainly: permeability and heterogeneity characterization parameters);

[0098] Step 5: Establish evaluation standards for geological characteristic parameters of water intrusion channels; classify each geological characteristic parameter into homogeneous, heterogeneous, and strongly heterogeneous categories according to the evaluation standards;

[0099] Step 6: Set the weights of the geological feature parameters for each region, and calculate the average probability attribute volume of the matrix and cracks respectively;

[0100] Step 7: By setting weights, the average probability attribute volumes of the matrix and cracks are fused into a maximum probability water intrusion channel distribution model. Then, by continuously adjusting the weights of the average probability attribute volumes of the matrix and cracks, a maximum probability water intrusion channel distribution model is calculated and determined.

[0101] Step 8: Perform numerical simulation on the model and ensure that the error between the calculation results and the production dynamics is less than 5%. Further improve the water intrusion channel distribution model by combining new drilling data.

[0102] Step 1 specifically includes:

[0103] (1) Establish a stratigraphic framework model by integrating seismic interpretation and well logging interpretation data of the study area.

[0104] (2) The matrix property model is established by using phase-controlled seismic inversion data volume as constraints, applying multi-well variation function analysis, and employing sequential indicator simulation method. The phase model is established by using Gaussian stochastic method with phase model as constraint, and deterministic simulation uses cokriging method with phase-controlled inversion porosity plane map as plane constraint. The matrix porosity model is obtained by combining the two methods.

[0105] (3) The fracture attribute model uses the imaging logging interpretation conclusions as the basic parameters to classify fractures according to their occurrence and sub-layers. The fracture prediction plan and fault distance volume are used as constraints to randomly simulate the fracture strength model. Then, the DFN (Discrete Fracture Network) model of various fractures is established through random simulation.

[0106] Step 2 specifically includes:

[0107] (1) Cross-plots were constructed for the porosity and permeability of different sedimentary microfacies in each sublayer, such as... Figure 3 As shown.

[0108] (2) The relevant power function was obtained by fitting the porosity-permeability relationship curve, as shown in Table 1:

[0109]

[0110] Where K is the permeability, mD; Φ is the porosity, decimal; and b1 is the coefficient obtained through fitting.

[0111] Table 1

[0112]

[0113]

[0114] (3) Using the power function described above, the permeability under different sedimentary microfacies in each sublayer is calculated to obtain the matrix permeability model, such as... Figure 4 As shown.

[0115] (4) Fracture permeability is the fracture aperture interpreted from imaging logging data. The inherent permeability of the fracture plate is calculated based on the fracture plane flow theory formula, as follows:

[0116]

[0117] Among them, K f b1 represents the permeability of the fractured section, in mD; b2 represents the fracture aperture, in μm.

[0118] Based on the calculation of fracture permeability, the Oda method is used to calculate the fracture permeability model, such as... Figure 5 As shown.

[0119] Step 3 specifically includes:

[0120] The heterogeneity characterization parameters of the matrix were obtained through the matrix permeability model, and the heterogeneity characterization parameters of the cracks were all obtained through the crack permeability model.

[0121] (1) Quantitative description of permeability surge coefficient in grid: The average permeability within the entire grid range is statistically analyzed, and the permeability surge coefficient of each grid is calculated using the following formula to complete the grid calculation.

[0122]

[0123] Among them, T K K represents the permeability surge coefficient for a single grid, dimensionless. n For the permeability of a single grid, mD; K mean denoted as mD, representing the average permeability across the entire grid range.

[0124] (2) Quantitative description of permeability range grid: The minimum permeability value within the entire grid range is statistically analyzed, and the permeability range of each grid is calculated using the following formula to complete the grid calculation.

[0125]

[0126] Among them, J K The permeability of a single grid is extremely poor and dimensionless; K n For the permeability of a single grid, mD; K min denoted as mD, represents the minimum permeability across the entire grid area.

[0127] (3) Quantitative description of permeability variation coefficient in grid: The average permeability within the entire grid range is statistically analyzed, and the permeability variation coefficient of each grid is calculated using the following formula to complete the grid calculation.

[0128]

[0129] Among them, V K K is the permeability variation coefficient for a single grid, dimensionless; n For the permeability of a single grid, mD; K mean denoted as mD, representing the average permeability across the entire grid area.

[0130] Matrix-crack permeability difference, permeability surge coefficient, and permeability variation coefficient are calculated using a gridded method. Figure 6 As shown.

[0131] The permeability in the water intrusion channel address characteristic parameters in step 4 is obtained through the matrix permeability model and the fracture permeability model.

[0132] In step 5, based on the frequency distribution histograms of various geological characteristic parameters, the permeability and heterogeneity characterization parameter values ​​are divided into three categories: homogeneous, heterogeneous, and strongly heterogeneous to describe the degree of heterogeneity between grids, as shown in Table 2 (evaluation criteria for geological characteristic parameters of matrix water intrusion dominant channels) and Table 3 (evaluation criteria for geological characteristic parameters of fracture water intrusion dominant channels).

[0133] Table 2

[0134] Geological characteristic parameters homogenization heterogeneous Strongly heterogeneous Penetration rate, mD ≤5 >5 and ≤50 >50 Permeability surge coefficient ≤1 >1 and ≤5 >5 Extremely poor penetration ≤10 >10 and ≤100 >100 Permeability variation coefficient ≤1 >1 and ≤5 >5

[0135] Table 3

[0136]

[0137] Step 6 specifically includes:

[0138] (1) Use core test permeability to correct the discretized permeability logging curve of a single well.

[0139] (2) Use the following formulas to verify the correlation coefficients between the discretized permeability logging curves of a single well and the various heterogeneous parameters of the matrix.

[0140]

[0141] Among them, U k The well logging permeability values ​​are discretized for a single well, in mD; H mk Cov(U) is a parameter representing the heterogeneity of a certain matrix. k H mk ) for U k With H mk covariance; Var[U k ] for U k The variance, Var[H mk ] is H mk The variance.

[0142] (3) Use the following formulas to verify the correlation coefficients between the single-well discretized fracture strength curve and each non-homogeneity parameter of the fracture.

[0143]

[0144] Among them, I f The fracture strength value is a discrete value for a single well and is dimensionless; H fk Cov(I) is a parameter representing the heterogeneity of a certain crack. f H fk ) for I f With H fk covariance; Var[I f ] for I f The variance, Var[H fk ] is Hfk Variance

[0145] (4) Set the weights of each geological feature parameter: If the correlation coefficient r is equal to 1, it proves 100% positive correlation, and the weight of this heterogeneity parameter is 1; if 0.5 ≤ r < 1, the weight of this heterogeneity parameter can be set to a value greater than 0.5 and less than 1; if 0 < r ≤ 0.5, the weight of this heterogeneity parameter is set to a value less than 0.5 and greater than 0; if the correlation coefficient r is equal to 0, it proves no correlation, and this heterogeneity parameter cannot be used to establish the average probability property body.

[0146] (5) Establish the average probability property bodies of the matrix and fractures respectively using the following formulas.

[0147]

[0148] Among them, is the weighted average of a single grid, mD; K n is the permeability of a single grid, mD; f1 is the weight of K n ; T k is the permeability breakthrough coefficient of a single grid, dimensionless; f2 is the weight of T k ; J k is the permeability breakthrough coefficient of a single grid, dimensionless; f3 is the weight of J k ; V k is the permeability variation coefficient of a single grid, dimensionless; f4 is the weight of V k ; P i is the average probability of a single grid; is the maximum weighted average among all grids statistically.

[0149] Among them, the average probability property bodies of the matrix and fractures are shown in Figure 7 and Figure 8 .

[0150] The formula for Step 7 is as follows:

[0151]

[0152] Among them, is the water invasion channel probability value of a single grid, decimal; P im is the average probability of a single grid in the matrix, decimal; y1 is the weight of P im ; P if is the average probability of a single grid in the fracture, decimal; y2 is the weight of P if ; weight.

[0153] In step 8, the historical fitting results show that the formation pressure fitting error is 0.47%, the daily gas production fitting error is zero, the wellhead oil pressure fitting error is 4.28%, and the daily water production fitting error is 4.5%. The model is highly accurate in spatial characterizing the dominant water intrusion channels in fractured-pore gas reservoirs, and the method is reliable.

[0154] Those skilled in the art should understand that, despite the detailed description of this disclosure with reference to the foregoing embodiments, modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure.

Claims

1. A method for spatial characterizing the water-dominant channels in fracture-pore gas reservoirs, characterized in that, The method includes: A fine geological model with dual media is established, which includes a matrix porosity model and a discrete fracture network model. The matrix permeability model is obtained based on the matrix porosity model, and the fracture permeability model is obtained based on the discrete fracture network model. Mesh generation of matrix heterogeneity characterization parameters based on matrix permeability model, and mesh generation of fracture heterogeneity characterization parameters based on fracture permeability model; Evaluation criteria for geological feature parameters of matrix water intrusion channels were constructed by gridding matrix heterogeneity characterization parameters, and evaluation criteria for geological feature parameters of fracture water intrusion channels were constructed by gridding fracture heterogeneity characterization parameters. The average probability attribute body of the matrix is ​​obtained based on the evaluation criteria of geological characteristic parameters of the matrix water intrusion channel, and the average probability attribute body of the fracture is obtained based on the evaluation criteria of geological characteristic parameters of the fracture water intrusion channel. The water intrusion channel distribution model is obtained based on the average probability attribute volume of the matrix and the average probability attribute volume of the cracks. The dominant water intrusion channels in the test area are then spatially characterized using the water intrusion channel distribution model to obtain the spatial characterization results.

2. The method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs according to claim 1, characterized in that, The matrix permeability model is derived from the matrix porosity model, including: Obtain the actual values ​​of porosity and permeability of different sedimentary microphases in each sublayer; A cross-plot is obtained by using the actual values ​​of porosity and permeability, and the cross-plot includes a curve showing the relationship between porosity and permeability; By fitting the porosity-permeability curve, a power function with respect to porosity is obtained; The predicted permeability values ​​under different sedimentary microfacies in each sublayer were obtained using power functions; A matrix permeability model is derived based on the predicted permeability value.

3. The method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs according to claim 1, characterized in that, The fracture permeability model is obtained based on the discrete fracture network model, including: Obtain the crack permeability; The Oda method was used to obtain a fracture permeability model.

4. The method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs according to claim 1, characterized in that, After meshing the matrix heterogeneity characterization parameters based on the matrix permeability model and the fracture heterogeneity characterization parameters based on the fracture permeability model, the following steps are taken: Dimensionless transformation of characteristic parameters of matrix and crack; The characteristic parameters include at least heterogeneity characterization parameters and permeability.

5. The method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs according to claim 1, characterized in that, The evaluation criteria for the geological characteristic parameters of the water intrusion channel include: homogeneous, heterogeneous, and strongly heterogeneous.

6. The method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs according to claim 1, characterized in that, The average probability attribute body of the matrix is ​​obtained based on the evaluation criteria of geological characteristic parameters of the matrix water intrusion channel, including: Core test permeability was used to correct discretized permeability logging curves of a single well. Verify the correlation coefficients between the discretized permeability logging curves of a single well and various heterogeneous parameters of the matrix; The weights of various geological characteristic parameters related to the matrix are set according to the correlation coefficient; The average probability attribute volume of the matrix is ​​obtained by using the weights of various geological characteristic parameters and permeability of the matrix.

7. The method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs according to claim 1, characterized in that, The average probability attribute body of fractures is obtained based on the evaluation criteria of geological characteristic parameters of fracture water intrusion channels, including: Core test permeability was used to correct the discretized fracture strength curve of a single well; Verify the correlation coefficients between the discretized fracture intensity curves of a single well and various heterogeneous parameters of the fracture; The weights of various geological characteristic parameters related to cracks are set according to the correlation coefficient; The average probability attribute body of the crack is obtained by using the weights of the geological characteristic parameters of the crack and the permeability.

8. The method for spatial characterization of water-dominant channels in fracture-pore gas reservoirs according to claim 1, characterized in that, The water intrusion channel distribution model is obtained based on the average probability attribute volume of the matrix and the average probability attribute volume of the fracture, including: The water intrusion channel distribution model is obtained based on the average probability attribute volume of the matrix, the average probability attribute volume of the crack, the weights of the geological characteristic parameters of the matrix, and the weights of the geological characteristic parameters of the crack.

9. A spatial characterization system for water-dominant channels in fracture-pore gas reservoirs, characterized in that, The system includes: A module is established to build a fine geological model of dual media, which includes a matrix porosity model and a discrete fracture network model. The first acquisition module is used to obtain the matrix permeability model based on the matrix porosity model and the fracture permeability model based on the discrete fracture network model. The meshing module is used for meshing matrix heterogeneity characterization parameters based on the matrix permeability model and for meshing fracture heterogeneity characterization parameters based on the fracture permeability model. The evaluation criteria module is used to construct evaluation criteria for geological feature parameters of matrix water intrusion channels by gridding matrix heterogeneity characterization parameters, and to construct evaluation criteria for geological feature parameters of fracture water intrusion channels by gridding fracture heterogeneity characterization parameters. The second acquisition module is used to obtain the matrix average probability attribute body based on the evaluation standard of geological characteristic parameters of matrix water intrusion channel, and to obtain the fracture average probability attribute body based on the evaluation standard of geological characteristic parameters of fracture water intrusion channel. The characterization module is used to obtain a water intrusion channel distribution model based on the average probability attribute volume of the matrix and the average probability attribute volume of the crack, and to spatially characterize the dominant water intrusion channels in the test area using the water intrusion channel distribution model to obtain spatial characterization results.

10. The spatial characterization system for water-intrusion dominant channels in fracture-pore gas reservoirs according to claim 9, characterized in that, The system also includes: The conversion module is used to perform dimensionless conversion of the characteristic parameters of the matrix and cracks; The characteristic parameters include at least heterogeneity characterization parameters and permeability.

11. The spatial characterization system for water-dominant channels in fracture-pore gas reservoirs according to claim 9, characterized in that, The second acquisition module is used to obtain the average probability attribute body of the matrix based on the evaluation criteria of geological characteristic parameters of the matrix water intrusion channel, including: The second acquisition module is used to correct the discretized permeability logging curves of a single well using core test permeability. Verify the correlation coefficients between the discretized permeability logging curves of a single well and various heterogeneous parameters of the matrix; The weights of various geological characteristic parameters related to the matrix are set according to the correlation coefficient; The average probability attribute volume of the matrix is ​​obtained by using the weights of various geological characteristic parameters and permeability of the matrix.

12. The spatial characterization system for water-dominant channels in fracture-pore gas reservoirs according to claim 9, characterized in that, The second acquisition module is used to obtain the average probability attribute body of fractures based on the evaluation criteria of geological characteristic parameters of fracture water intrusion channels, including: The second acquisition module is used to correct the discrete fracture strength curve of a single well using the permeability of core experiments. Verify the correlation coefficients between the discretized fracture intensity curves of a single well and various heterogeneous parameters of the fracture; The weights of various geological characteristic parameters related to cracks are set according to the correlation coefficient; The average probability attribute body of the crack is obtained by using the weights of the geological characteristic parameters of the crack and the permeability.

13. The spatial characterization system for water-intrusion dominant channels in fracture-pore gas reservoirs according to claim 9, characterized in that, The characterization module, used to obtain a water intrusion channel distribution model based on the matrix average probability attribute volume and the crack average probability attribute volume, includes: The characterization module is used to obtain the water intrusion channel distribution model based on the matrix average probability attribute volume, the crack average probability attribute volume, the weights of various geological characteristic parameters related to the matrix, and the weights of various geological characteristic parameters related to the crack.

Images