Phase control-based classification and evaluation method, equipment, and medium for favorable oil and gas exploration areas

Abstract

Embodiments of the present invention disclose a phase-controlled, favorable oil and gas exploration zone classification and evaluation method, device, and medium. The phase-controlled favorable oil and gas exploration zone classification and evaluation method includes: determining a favorable oil and gas exploration zone and dividing the zone into multiple grids; establishing a phase-controlled favorable zone classification and evaluation standard to obtain a grid standard; establishing an uncertainty simulation model based on small-cell control; simulating the grid resource volume based on the grid standard and the small-cell control-based uncertainty simulation model; and evaluating the favorable oil and gas exploration zone based on the simulated resource volume. This method reduces errors and accurately predicts the location of the favorable oil and gas exploration zone.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration, and more specifically, relates to a phase control-based classification and evaluation method, equipment, and medium for oil and gas exploration favorable areas. Background Art

[0002] With the continuous intensification of my country's oil and gas resource exploration efforts, deepening geological understanding, and the continuous expansion of exploration areas, many exploration "forbidden zones" have been broken through, and many new areas and types have been discovered. In particular, the rapid rise of unconventional oil and gas in recent years has significantly increased the types of resources, and the resource structure and understanding are changing.

[0003] Generally speaking, unconventional continuous oil and gas accumulations are defined as those with a vast spatial distribution, no clear boundaries, and a degree of independence from water column pressure. Schmoker (1996) and Schmoler et al. (1996) have respectively conducted detailed studies and descriptions of the geological and production characteristics of continuous oil and gas accumulations. Continuous oil and gas accumulations share the following common characteristics: downdip location from water-saturated rocks, the absence of distinct traps and caprocks, diffuse oil and gas injection, widespread distribution, low matrix permeability, abnormal pressures (ultrahigh or ultralow), and associated source rocks. Due to the fundamental geological differences between unconventional and conventional oil and gas accumulations, international organizations (such as the United States Geological Survey) have employed different models and methods for resource evaluation of these two types of accumulations. When evaluating the resources of unconventional oil and gas accumulations, we cannot, like conventional oil and gas accumulations, divide the oil and gas accumulations into independent oil and gas reservoirs based on the oil (gas)-water interface in the downdip direction and evaluate their resource volume based on the number and size of the oil and gas reservoirs.

[0004] Currently, the volumetric method is the primary method for quantitatively evaluating unconventional oil and gas resources in China. This method is simple and widely used. It primarily uses parameters such as reservoir thickness, porosity, and oil saturation to determine resource abundance. The volumetric method employs a minimal evaluation process and simple input parameters, making it suitable for resource estimation in the early stages of oil and gas exploration.

[0005] Existing volumetric methods are unable to characterize the heterogeneity of key parameters such as porosity and oil saturation. Single values ​​for each parameter yield relatively holistic and summary assessments of the evaluation area, failing to reflect the variability in resource abundance distribution across a given surface. Because unconventional oil and gas reservoirs are characterized by large, continuous accumulations and wide variations in oil and gas resource abundance, using average values ​​is prone to significant errors and cannot accurately predict the location of favorable areas for oil and gas exploration. Summary of the Invention

[0006] In view of this, the embodiments of the present invention provide a phase-controlled based method, device and medium for grading and evaluating favorable oil and gas exploration areas, which at least solves the problem in the prior art of large errors and inability to accurately predict the location of favorable oil and gas exploration areas.

[0007] In a first aspect, an embodiment of the present invention provides a method for evaluating and grading favorable oil and gas exploration areas based on phase control, comprising:

[0008] determining an area favorable for oil and gas exploration, and dividing the area into grids to obtain a plurality of grids;

[0009] Establish a grading evaluation standard for favorable areas based on phase control and obtain the grid standard;

[0010] Establish an uncertainty simulation model based on small-surface control;

[0011] Simulating the resource quantity of the grid based on the grid standard and the uncertainty simulation model based on small cell control;

[0012] Based on the simulated resource volume, favorable areas for oil and gas exploration are evaluated.

[0013] Optionally, the determining of an area favorable for oil and gas exploration and gridding the area to obtain a plurality of grids may include:

[0014] The areas of favorable areas for oil and gas exploration are determined using overlay analysis, which includes intersection-based overlay analysis and / or erasure-based overlay analysis.

[0015] Optionally, the gridding the area includes:

[0016] GIS-based regular grid division and / or well control-based Thiessen polygon division.

[0017] Optionally, establishing a phase-controlled favorable zone classification evaluation standard includes:

[0018] Establishing the analysis and evaluation criteria for the main controlling factors;

[0019] Construct geological models and functions;

[0020] Based on the evaluation criteria and geological models and functions, single factor analysis based on facies control is carried out;

[0021] A phase-controlled multifactor hierarchical superposition evaluation was performed based on the phase-controlled univariate analysis results.

[0022] Optionally, the superposition evaluation includes superposition analysis based on the main controlling factors of reservoir formation;

[0023] The superposition analysis based on the main controlling factors of reservoir formation includes: superposition of the main controlling factors.

[0024] Optionally, the superposition of the main control factors includes projecting the spatial analysis results of each main control factor onto a unified two-dimensional plane system to obtain a two-dimensional plane;

[0025] The two-dimensional plane is discretized using a preconfigured uniform grid.

[0026] Optionally, the superposition of the main controlling factors includes:

[0027] Assume T is the number of main control factors, and use n×n discrete grid. Represents the analytical value of the main control factor t at the grid point (i, j), defined as:

[0028]

[0029] It is called the indicator value of the main control factor t at the grid point (i, j);

[0030] The indicator value of the main control factor t forms a matrix on a two-dimensional discrete grid:

[0031]

[0032] The T main controlling factors are superimposed as follows:

[0033]

[0034] is the indicator value of T main control factors at the grid point (i, j);

[0035] The final superposition result is:

[0036]

[0037] Where m and n are natural numbers, The grid whose element value is equal to 1 is the superposition unit that meets the conditions.

[0038] Optionally, the establishing of an uncertainty simulation model based on small-surface control includes:

[0039] Construct a small patch volume method model considering the enrichment probability and mining probability:

[0040]

[0041] Qi=Q 吸 +Q 游 =P g ×P e ×S i ×h i ×ρ×G / 100,

[0042] Q is the total geological resources; Q i is the natural gas geological resources in the unit grid; Q 吸 is the amount of adsorbed gas geological resources in the unit grid; Q 游 is the free gas geological resources in the unit grid; P g is the shale gas enrichment probability of the unit grid; P e is the economic recoverability probability of shale gas in the unit grid; S i is the unit grid area; H i is the thickness of gas-bearing mudstone in the unit grid; ρ is the density of mudstone; G is the gas content in the unit grid, and n is the number of effective grids.

[0043] In a second aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0044] a memory storing executable instructions;

[0045] A processor, wherein the processor runs the executable instructions in the memory to implement the phase control-based classification and evaluation method for favorable oil and gas exploration areas according to any one of the first aspects.

[0046] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the phase control-based classification and evaluation method for favorable oil and gas exploration areas as described in any one of the first aspects.

[0047] The present invention evaluates favorable oil and gas exploration areas by identifying them, dividing them into multiple grids, establishing grid standards and an uncertainty simulation model based on small-surface control, and simulating the resource volume of the grids based on the model. This approach reduces errors and accurately predicts the location of favorable oil and gas exploration areas.

[0048] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0050] Figure 1 A flow chart showing a method for evaluating the classification of favorable oil and gas exploration areas based on phase control according to an embodiment of the present invention is shown;

[0051] Figure 2A principle block diagram showing a method for evaluating the classification of favorable oil and gas exploration areas based on phase control according to an embodiment of the present invention is shown;

[0052] Figure 3a A schematic diagram showing the boundary range controlled by the semi-deep lake phase in the Sichuan Basin according to an embodiment of the present invention is shown;

[0053] Figure 3b A schematic diagram showing the boundary range controlled by the debris beach facies in the Sichuan Basin according to an embodiment of the present invention is shown;

[0054] Figure 4 A schematic diagram of RO contour distribution in the Sichuan Basin according to an embodiment of the present invention is shown;

[0055] Figure 5 A schematic diagram showing the superimposed distribution of semi-deep lake phases and RO contour lines in the Sichuan Basin according to an embodiment of the present invention is shown;

[0056] Figure 6 A schematic diagram showing the superimposed distribution of debris shoal phase and RO contour lines in the Sichuan Basin according to an embodiment of the present invention is shown;

[0057] Figure 7 A schematic diagram illustrating the distribution range analysis of debris shoal phases with an RO greater than 1.3 in the Sichuan Basin according to an embodiment of the present invention is shown;

[0058] Figure 8 A schematic diagram of favorable zone classification evaluation based on facies control in the Sichuan Basin according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0059] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0060] like Figure 1 As shown, a method for evaluating the favorable zones for oil and gas exploration based on phase control includes:

[0061] Step S101: determining an area favorable for oil and gas exploration, and dividing the area into grids to obtain a plurality of grids;

[0062] Step S102: establishing a favorable zone classification evaluation standard based on phase control to obtain a grid standard;

[0063] Step S103: establishing an uncertainty simulation model based on small-surface control;

[0064] Step S104: simulating the resource quantity of the grid based on the grid standard and the uncertainty simulation model based on small-surface control;

[0065] Step S105: Evaluate favorable areas for oil and gas exploration based on the resource quantities obtained through simulation.

[0066] Optionally, the determining of an area favorable for oil and gas exploration and gridding the area to obtain a plurality of grids may include:

[0067] The areas of favorable areas for oil and gas exploration are determined using overlay analysis, which includes intersection-based overlay analysis and / or erasure-based overlay analysis.

[0068] Optionally, the gridding the area includes:

[0069] GIS-based regular grid division and / or well control-based Thiessen polygon division.

[0070] Optionally, establishing a phase-controlled favorable zone classification evaluation standard includes:

[0071] Establishing the analysis and evaluation criteria for the main controlling factors;

[0072] Construct geological models and functions;

[0073] Based on the evaluation criteria and geological models and functions, single factor analysis based on facies control is carried out;

[0074] A phase-controlled multifactor hierarchical superposition evaluation was performed based on the phase-controlled univariate analysis results.

[0075] Optionally, the superposition evaluation includes superposition analysis based on the main controlling factors of reservoir formation;

[0076] The superposition analysis based on the main controlling factors of reservoir formation includes: superposition of the main controlling factors.

[0077] Optionally, the superposition of the main control factors includes projecting the spatial analysis results of each main control factor onto a unified two-dimensional plane system to obtain a two-dimensional plane;

[0078] The two-dimensional plane is discretized using a preconfigured uniform grid.

[0079] Optionally, the superposition of the main controlling factors includes:

[0080] Assume T is the number of main control factors, and use m×n discrete grid. Represents the analytical value of the main control factor t at the grid point (i, j), defined as:

[0081]

[0082] It is called the indicator value of the main control factor t at the grid point (i, j);

[0083] The indicator value of the main control factor t forms a matrix on a two-dimensional discrete grid:

[0084]

[0085] The T main controlling factors are superimposed as follows:

[0086]

[0087] is the indicator value of T main control factors at the grid point (i, j);

[0088] The final superposition result is:

[0089]

[0090] Where m and n are natural numbers, The grid whose element value is equal to 1 is the superposition unit that meets the conditions.

[0091] Optionally, the establishing of an uncertainty simulation model based on small-surface control includes:

[0092] Construct a small patch volume method model considering the enrichment probability and mining probability:

[0093]

[0094] Qi=Q 吸 +Q 游 =P g ×P e ×S i ×h i ×ρ×G / 100,

[0095] Q is the total geological resources; Q i is the natural gas geological resources in the unit grid; Q 吸 is the amount of adsorbed gas geological resources in the unit grid; Q 游 is the free gas geological resources in the unit grid; P g is the shale gas enrichment probability of the unit grid; P e is the economic recoverability probability of shale gas in the unit grid; S i is the unit grid area; H i is the thickness of gas-bearing mudstone in the unit grid; ρ is the density of mudstone; G is the gas content in the unit grid, and n is the number of effective grids.

[0096] Example 1:

[0097] like Figure 2As shown in the figure, favorable area evaluation and resource calculation are important tasks in oil and gas exploration. The focus is to establish reasonable evaluation standards and geological models based on existing reservoir-forming conditions, construct mathematical functions based on geological models, and use spatial GIS and other technical means to evaluate favorable areas and calculate resource potential.

[0098] The main processes include: 1. Evaluation unit division and effective range determination; 2. Facies-based favorable zone hierarchical evaluation and function construction; 3. Uncertainty Montessori simulation resource processing based on small-surface control.

[0099] 1. Determination of the effective scope of the evaluation unit:

[0100] Taking the evaluation of favorable shale gas zones as an example, the starting range for shale oil and gas favorable zone evaluation must first be determined based on the evaluation criteria. According to existing standards and specifications, this range is usually defined based on the continuous thickness of organic-rich shale.

[0101] Starting standard 1: When TOC ≥ 0.5%, the cumulative thickness of shale is greater than 30m;

[0102] Starting standard 2: When TOC ≥ 1.0%, the continuous thickness of shale is greater than 10m;

[0103] Starting standard 3: When TOC ≥ 2.0%, the continuous thickness of shale is greater than 5m;

[0104] Therefore, it is necessary to study the TOC plane distribution map and shale thickness map of the evaluation area based on the above different starting standards.

[0105] First, based on the TOC (total organic carbon) plane distribution diagram of the evaluation area, determine the range S where TOC is greater than 0.5. TOC0.5 At the same time, determine the range of thickness greater than 30m in the shale thickness map S h30 The effective overlap range of the two is the range S of the starting condition 1. TOC0.5 h30 .

[0106] According to the starting condition 2, determine the range S where TOC is greater than 1 for the TOC plane layout diagram of the evaluation area. TOC1 At the same time, determine the range of thickness greater than 10m in the shale thickness map S h10 The effective overlapping range of the two is the range S of the starting condition 2 TOC1 h10 .

[0107] According to the starting condition 3, determine the range S where TOC is greater than 2 for the TOC plane layout diagram of the evaluation area. TOC2 At the same time, determine the range of thickness greater than 5m in the shale thickness map S h5 The effective overlap range of the two is the range S of the starting condition 3. TOC2 h5 .

[0108] The optimal evaluation range is the combined range determined by the starting conditions 1, 2, and 3: S = S TOC0.5 h30 +S TOC1 h10 +S TOC2 h5 .

[0109] After the evaluation scope is determined, the evaluation scope is gridded and used as the grid unit standard for subsequent graded evaluation.

[0110] 2. Favorable zone classification evaluation based on phase control:

[0111] The hierarchical evaluation of favorable areas based on phase control is based on the study of the main controlling factors of shale oil and gas accumulation and the establishment of an evaluation parameter system. The core is the superposition analysis based on the main controlling factors of accumulation.

[0112] To superimpose the main controlling factors, first, it is necessary to project the spatial analysis results of each main controlling factor onto a unified two-dimensional plane system, and secondly, discretize the two-dimensional plane using a unified grid.

[0113] Assume T is the number of main control factors, and use m×n discrete grid. Represents the analytical value of the main control factor t at the grid point (i, j), defined as:

[0114]

[0115] It is called the indicator value of the main control factor t at the grid point (i, j).

[0116] The indicator value of the main control factor t forms a 0-1 matrix on a two-dimensional discrete grid:

[0117]

[0118] In this way, the superposition of T main control factors can be completed by performing the following operations on the 0-1 matrix:

[0119]

[0120] are the indicator values ​​of the T main control factors at the grid point (i, j).

[0121] The final superposition result can also be expressed as a 0-1 matrix:

[0122]

[0123] The grid whose element value is equal to 1 is the superposition unit that meets the conditions.

[0124] Based on the research on the main controlling factors of shale oil and gas, the main controlling factors for the evaluation of favorable areas include multiple parameters, including sedimentary facies, source rock thickness, organic carbon content, maturity, burial depth, etc. An evaluation standard system corresponding to the main controlling factors is established, as shown in Table 1.

[0125] Table 1. Evaluation standard system corresponding to main control factors

[0126]

[0127] Because sedimentary phases have a strong control over the enrichment of shale oil and gas, it is necessary to consider the combined relationship between various controlling factors and different lithofacies when evaluating favorable areas. First, based on sedimentary facies research, different facies zones are divided and evaluated.

[0128] For example, the Da'anzhai sedimentary facies in the Sichuan Basin includes five types: semi-deep lake, carbonate shallow lake, lakeshore, fan delta, and shell-shoal. The first type of sedimentary facies is semi-deep lake and shell-shoal; the second type is carbonate shallow lake; and the third type is lakeshore and fan delta.

[0129] According to the different types of sedimentary facies, they are combined with the selected main controlling factors. Take the thermal evolution degree of Da'anzhai in Sichuan Basin as an example. Figure 3a 、 Figure 3b and Figure 4 shown.

[0130] First, the plane distribution range of the thermal evolution degree is split according to different phase zones, including semi-deep lake, debris beach, and shallow lake. The splitting results are as follows: Figure 5 and Figure 6 shown.

[0131] According to the thermal evolution degree of different phase zones after splitting, the thermal evolution degree of the phase zones is graded and evaluated according to the main control factor evaluation criteria in Table 1. For example, for the thermal evolution degree of the debris beach, the area with RO greater than 1.3 is analyzed as a favorable area, and research and evaluation are carried out. The results are as follows Figure 7 shown.

[0132] Finally, based on the analysis and superposition of multiple main controlling factors controlled by sedimentary facies, the favorable zone classification evaluation result map of the study area was obtained, as shown in the following figure: Figure 8 shown.

[0133] 3. Uncertain Montessori simulation of resource quantity based on small facet control

[0134] On the basis of determining the scope of the favorable area, in order to overcome the uncertainty of shale gas evaluation parameters and ensure the scientific rationality of the evaluation results, this volume method is based on a spatially continuous and uniformly distributed geological model to establish a probability distribution model for different calculation parameters.

[0135] Among them, the small patch volume method model considering the enrichment probability and mining probability is:

[0136]

[0137] Q i =Q 吸 +Q 游 =P g ×P e ×S i ×h i ×ρ×G / 100,

[0138] in:

[0139] Q is the total geological resources (10 8 m 3 );Q i is the natural gas geological resources of the unit grid (10 8 m 3 );

[0140] Q 吸 is the adsorbed gas geological resources of the unit grid (10 8 m 3 );Q 游 is the free gas geological resources in the unit grid (10 8 m 3 );P g is the probability of shale gas enrichment in the unit grid (decimal); P e is the probability of economic recovery of shale gas in the unit grid (decimal); S i is the unit grid area (km 2 );H i is the thickness of gas-bearing mudstone in the unit grid (m);

[0141] ρ is the density of shale (t / m 3 ); G is the gas content of the unit grid (the sum of the adsorbed gas content and the free gas content, m 3 / t), n is the number of effective grids.

[0142] Based on the geological model and the defined evaluation unit boundaries, the resource volume is simulated for each grid cell according to the aforementioned grid standards. The number and size of the grid cells can be determined based on the size of the evaluation unit and the level of data available. The grid shape can be a regular rectangle or a Thiessen polygon based on the well distribution. Alternatively, each square kilometer or square meter can be used as a grid cell, where each grid cell represents the resource volume per unit area, i.e., the resource abundance.

[0143] Based on grid division, Monte Carlo simulation can be used to obtain the spatial resource quantity and resource abundance distribution.

[0144] This example, based on the determination of the effective range, comprehensively considers multiple key controlling factors and evaluates each individual key controlling factor for reservoir formation, primarily focusing on sedimentary facies, to obtain a hierarchical evaluation of favorable areas. Based on these hierarchical evaluation results, a grid-based Monte Carlo simulation of small-cell resource quantities was performed. The results better meet the needs of actual exploration work and can effectively support research on exploration deployment decisions.

[0145] Example 2:

[0146] An embodiment of the present invention provides an electronic device including a memory and a processor.

[0147] a memory storing executable instructions;

[0148] The processor runs the executable instructions in the memory to implement a phase control-based classification and evaluation method for favorable oil and gas exploration areas.

[0149] The memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc.

[0150] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0151] Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience, this embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the scope of protection of the present invention.

[0152] For detailed description of this embodiment, please refer to the corresponding description in the aforementioned embodiments, which will not be repeated here.

[0153] Example 3:

[0154] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, a method for evaluating the classification of favorable oil and gas exploration areas based on phase control is implemented.

[0155] The computer-readable storage medium according to an embodiment of the present invention stores non-transitory computer-readable instructions, which, when executed by a processor, execute all or part of the steps of the aforementioned methods of the various embodiments of the present invention.

[0156] The above-mentioned computer-readable storage media include, but are not limited to, optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or mobile hard disks), media with built-in rewritable non-volatile memory (e.g., memory cards), and media with built-in ROM (e.g., ROM cartridges).

[0157] While various embodiments of the present invention have been described above, the above description is intended to be illustrative, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for evaluating the classification of favorable areas for oil and gas exploration based on phase control, characterized in that: include: determining an area favorable for oil and gas exploration, and dividing the area into grids to obtain a plurality of grids; Establish a grading evaluation standard for favorable areas based on phase control and obtain the grid standard; Establish an uncertainty simulation model based on small-surface control; Simulating the resource quantity of the grid based on the grid standard and the uncertainty simulation model based on small cell control; Evaluate favorable areas for oil and gas exploration based on the simulated resource quantities; The establishment of a phase-controlled favorable zone classification evaluation standard includes: Establishing the analysis and evaluation criteria for the main controlling factors; Construct geological models and functions; Based on the evaluation criteria and geological models and functions, single factor analysis based on facies control is carried out; A phase-controlled multi-factor hierarchical superposition evaluation was performed based on the phase-controlled univariate analysis results; The superposition evaluation includes superposition analysis based on the main controlling factors of reservoir formation; The superposition analysis based on the main controlling factors of reservoir formation includes: superposition of the main controlling factors; The superposition of the main controlling factors includes: Assume T is the number of main control factors, and use m×n discrete grid. Represents the analytical value of the main control factor t at the grid point (i, j), defined as: It is called the indicator value of the main control factor t at the grid point (i, j); The indicator value of the main control factor t forms a matrix on a two-dimensional discrete grid: The T main controlling factors are superimposed as follows: is the indicator value of T main control factors at the grid point (i, j); The final superposition result is: Where m and n are natural numbers, The grid whose element value is equal to 1 is the superposition unit that meets the conditions.

2. The method for evaluating favorable oil and gas exploration areas based on phase control according to claim 1, characterized in that: The method of determining a favorable area for oil and gas exploration and dividing the area into grids to obtain a plurality of grids includes: The areas of favorable areas for oil and gas exploration are determined using overlay analysis, which includes intersection-based overlay analysis and / or erasure-based overlay analysis.

3. The method for evaluating favorable oil and gas exploration areas based on phase control according to claim 1, characterized in that: The gridding of the area includes: GIS-based regular grid division and / or well control-based Thiessen polygon division.

4. The method for evaluating favorable oil and gas exploration areas based on phase control according to claim 1, characterized in that: The superposition of the main control factors includes projecting the spatial analysis results of each main control factor onto a unified two-dimensional plane system to obtain a two-dimensional plane; The two-dimensional plane is discretized using a preconfigured uniform grid.

5. The method for evaluating favorable oil and gas exploration areas based on phase control according to claim 1, characterized in that: The establishment of an uncertainty simulation model based on small-surface control includes: Construct a small patch volume method model considering the enrichment probability and mining probability: Q i =Q suction + Q travel = Pg × P e ×S i ×H i ×ρ×G / 100, Q is the total geological resources; Q i is the natural gas geological resources in the unit grid; Q 吸 is the amount of adsorbed gas geological resources in the unit grid; Q 游 is the free gas geological resources in the unit grid; P g is the shale gas enrichment probability of the unit grid; P e is the economic recoverability probability of shale gas in the unit grid; S i is the unit grid area; H i is the thickness of gas-bearing mudstone in the unit grid; ρ is the density of mudstone; G is the gas content in the unit grid, and n is the number of effective grids.

6. An electronic device, characterized in that: The electronic device comprises: a memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the phase control-based favorable area classification and evaluation method for oil and gas exploration according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for evaluating the classification of favorable oil and gas exploration areas based on phase control according to any one of claims 1 to 5 is implemented.

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