Beneficial area evaluation method, electronic device, apparatus, and storage medium

Abstract

The application discloses a favorable area optimization evaluation method, electronic equipment, a device and a storage medium, wherein the evaluation method comprises the following steps: determining the lithology and rock type of a target layer, analyzing the sedimentary environment and sedimentary facies of the target layer; establishing a high-frequency sequence framework of the target layer; analyzing the plane distribution of sedimentary microfacies; determining a favorable gas-bearing unit; according to the physical property standard of reservoir classification evaluation, evaluating and classifying the single-well reservoir physical property logging interpretation result, and listing the reservoir classification evaluation type result in well-to-well sedimentary microfacies correlation, analyzing the relationship between the reservoir type and the high-frequency sequence and the sedimentary microfacies, based on the constraint of the high-frequency sequence framework, combining the lateral distribution characteristics of the favorable sedimentary microfacies of the reservoir development, completing the lateral correlation and plane distribution analysis of the classified gas-bearing reservoir, and determining the favorable gas-bearing physical property unit; combining the geology, gas reservoir engineering and economic evaluation, establishing a gas reservoir favorable area optimization evaluation standard, carrying out the favorable area optimization, and determining the favorable development selection unit.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development technology, and in particular to a method for evaluating the selection of favorable areas, electronic equipment, apparatus and storage medium. Background Technology

[0002] The selection and evaluation of favorable development areas are fundamental to gas field development planning and production capacity construction. The size and reserve abundance of favorable areas determine the scale of development plans and production capacity construction. Differences in reservoir quality are the most important reason for differences in gas well productivity and a crucial basis for well location deployment. The ultimate goal of reservoir research is to classify and evaluate reservoirs in accordance with geological realities. As oilfield exploration and development deepens, reservoir evaluation is receiving increasing attention from experts both domestically and internationally.

[0003] Given the rapid vertical and horizontal variations, complex and diverse rock types, and strong heterogeneity of braided fluvial gas reservoirs, previous researchers have conducted extensive work on the selection of development sites for this type of reservoir. For example, considering the narrow lateral extension, discontinuous spatial distribution, low porosity, and low permeability of the target reservoir layer in the Lower Shihezi Formation of the Sulige Gas Field, previous researchers, based on the fine division of sedimentary microfacies and prediction of their spatial distribution, utilized sedimentary model-constrained sand body identification and gas-bearing detection, and the study of structural inversion during the hydrocarbon expulsion period and its relationship with the distribution of reservoirs and dissolution zones. By comprehensively considering the distribution of sedimentary microfacies, dissolution zones, and favorable paleostructures during the hydrocarbon expulsion period, they proposed the selection criteria for relatively enriched blocks in the Sulige Gas Field, and on this basis, selected relatively enriched blocks in the Sulige Gas Field (Lan Chaoli et al., 2008).

[0004] However, the evaluation of favorable development areas is influenced by numerous factors, including geology, reservoir engineering productivity evaluation, and economic evaluation. Both human factors in parameter selection and the accuracy of block data can significantly impact the evaluation. Furthermore, the standards and parameters for selecting favorable development areas vary considerably from region to region. Commonly used evaluation indicators include reservoir porosity and permeability, in addition to parameters such as gas saturation and effective thickness. Moreover, current evaluations of favorable development areas are mostly based on single qualitative or quantitative analyses, with limited comprehensive consideration of various factors.

[0005] Currently, a significant portion of the reserves in low-permeability tight clastic rock reservoirs is difficult to develop economically and effectively due to limitations in current engineering technology and economic conditions. Therefore, identifying locally high-yield, enriched areas that can achieve current economic benefits and optimizing development targets are the main challenges facing the development of low-permeability gas fields. Existing oil and gas reservoir selection and evaluation methods are mainly qualitative and single-factor evaluations, often resulting in overlapping and non-unique outcomes, and are poorly applicable to low-permeability lithologic gas reservoirs.

[0006] Therefore, we look forward to a method for evaluating favorable areas that can solve the problem of selecting favorable target areas for low-permeability lithologic gas reservoirs and provide a basis for decision-making in the efficient development of gas fields. Summary of the Invention

[0007] The purpose of this invention is to propose a method, electronic device, apparatus, and storage medium for evaluating favorable areas, which can solve the problem of selecting favorable target areas in low-permeability lithologic gas reservoirs and provide a decision-making basis for the efficient development of gas fields.

[0008] To achieve the above objectives, the present invention provides a method for evaluating the optimal selection of advantageous areas, comprising:

[0009] Step 1: Analyze the core and thin sections of the target layer to determine the lithology and rock type of the target layer, and analyze the sedimentary environment and sedimentary facies of the target layer in conjunction with the regional sedimentary background;

[0010] Step 2: Based on the analysis results of Step 1, establish the target layer high-frequency sequence lattice;

[0011] Step 3: Using the high-frequency stratigraphic framework, the target layer is divided into target sub-layers. Under the analysis constraints of the comprehensive response characteristics of well logging facies and seismic facies, the planar distribution of sedimentary microfacies with the target sub-layer as the unit is analyzed to determine the favorable lithological units of the gas reservoir.

[0012] Step 4: Based on the high-frequency sequence framework established in Step 2 and the planar distribution of sedimentary microfacies in Step 3, determine the favorable gas-bearing units in the favorable lithological units of the gas reservoir;

[0013] Step 5: Based on the favorable gas-bearing units determined in Step 4, evaluate and classify the reservoir physical property logging interpretation results of single wells according to the reservoir classification evaluation physical property standards, and list the reservoir classification evaluation type results in the well-connected sedimentary microfacies comparison, analyze the relationship between reservoir type and high-frequency sequence stratigraphy and sedimentary microfacies, and based on the constraints of the high-frequency sequence stratigraphy framework, combined with the lateral distribution characteristics of favorable sedimentary microfacies in reservoir development, complete the lateral comparison and planar distribution analysis of classified gas-bearing reservoirs, and determine the favorable gas-bearing physical property units;

[0014] Step 6: Based on the favorable gas-bearing physical property units, combine geology, gas reservoir engineering and economic evaluation to establish a selection evaluation standard for favorable gas reservoir areas, carry out the selection of favorable areas, and determine favorable development selection units.

[0015] According to a preferred embodiment of the present invention, the establishment of the high-frequency sequence framework of the target layer includes: combining and calibrating the selected logging curves based on the analysis results of step 1 to obtain lithology-sensitive curves and their lithology-sensitive variation characteristics; using the lithology-sensitive variation characteristics of the lithology-sensitive curves to identify marker layers and high-frequency sequence interfaces, and to calibrate logging facies and seismic facies; and using the identification results and the calibration results, establishing the high-frequency sequence framework of the target layer through a combination of well and seismic analysis.

[0016] According to a specific embodiment of the present invention, obtaining lithology-sensitive curves and their lithology-sensitive change characteristics includes: selecting multiple logging curves, combining and calibrating the multiple logging curves based on the lithology analysis results of the core and thin sections, determining the response characteristics of various logging curves for different lithologies, finding logging curves sensitive to lithology from the logging curve combinations as lithology-sensitive curves, and taking the change trend with lithology as lithology-sensitive change characteristics.

[0017] Preferably, the method for obtaining the well-connected sedimentary micro-facies comparison includes: using the high-frequency sequence framework established in step 2 and the seismic facies response characteristics in step 3 as constraints for the lateral comparison of sedimentary microfacies, to complete the well-connected sedimentary micro-facies comparison of the target layer.

[0018] According to a preferred embodiment of the present invention, step 4 includes: using the reservoir fluid logging interpretation results, placing the logging fluid interpretation results in the well-connected sedimentary microfacies comparison; based on the high-frequency sequence grid established in step 2 and the sedimentary microfacies planar distribution in step 3, drawing a gas reservoir profile using a combination of well and seismic logging; analyzing the factors controlling the gas and water distribution based on the gas and water distribution characteristics; determining the gas and water distribution boundaries of the gas-bearing unit; and determining favorable planar gas-bearing units.

[0019] Specifically, determining the gas-water distribution boundary of the gas-bearing unit includes: using the structural depth line corresponding to the boundary between the gas layer and the water layer in a single well as the boundary, the lithological boundary of the interconnected sand bodies under the constraints of reservoir geomorphological prediction is the water layer boundary, and the lithological boundary is used to determine the gas layer boundary in the structural high part.

[0020] Preferably, step 4 further includes: using favorable gas-bearing units as constraints and well point gas thickness data as a basis, combining well and seismic measurements to complete the planar distribution of gas-bearing reservoir thickness.

[0021] Another disclosed embodiment of the present invention also provides an electronic device, the electronic device comprising:

[0022] At least one processor; and,

[0023] A memory communicatively connected to the at least one processor; wherein,

[0024] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the aforementioned advantageous area selection evaluation method.

[0025] Another embodiment of the present invention also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the above-described advantageous area selection evaluation method.

[0026] Another disclosed embodiment of the present invention provides an advantageous area selection evaluation device, comprising:

[0027] The target layer sedimentation module is used to analyze the core and thin sections of the target layer, determine the lithology and rock type of the target layer, and analyze the sedimentary environment and sedimentary facies of the target layer in combination with the regional sedimentary background.

[0028] A high-frequency layer sequence grid module, wherein the high-frequency layer sequence grid is used to establish a high-frequency layer sequence grid for the target layer;

[0029] Favorable lithological unit module, which is used to divide the target layer into target sublayers using the high-frequency stratigraphic framework, and under the analysis constraints of the comprehensive response characteristics of well logging facies and seismic facies, analyze the planar distribution of sedimentary microfacies with the target sublayer as the unit, and determine the favorable lithological unit of the gas reservoir;

[0030] A favorable gas-containing unit module, wherein the favorable gas-containing unit is used to determine favorable gas-containing units;

[0031] The favorable gas-bearing physical property module is used to evaluate and classify the logging interpretation results of single-well reservoir physical properties according to the physical property standards for reservoir classification and evaluation, and to list the reservoir classification and evaluation type results in the well-connected sedimentary micro-facies comparison. It analyzes the relationship between reservoir type and high-frequency sequence stratigraphy and sedimentary microfacies. Based on the constraints of the high-frequency sequence stratigraphy framework and combined with the lateral distribution characteristics of favorable sedimentary microfacies in reservoir development, it completes the lateral comparison and planar distribution analysis of classified gas-bearing reservoirs and determines favorable gas-bearing physical property units.

[0032] The favorable development area selection module is used to combine geology, gas reservoir engineering and economic evaluation based on the favorable gas-bearing physical property units, establish the evaluation criteria for the selection of favorable gas reservoir areas, carry out the selection of favorable areas, and determine favorable development area selection units.

[0033] The beneficial effects of this invention are as follows:

[0034] This invention, based on high-frequency sequence stratigraphy-constrained reservoir correlation evaluation, establishes evaluation criteria for favorable development areas through comprehensive geological research and combined with gas reservoir engineering production capacity and economic evaluation results. By integrating well and seismic data, it completes the selection of favorable development areas, ultimately providing a highly operable method for this purpose. This addresses the challenges of complex water-bearing, low-permeability clastic gas reservoirs, which exhibit rapid vertical and horizontal variations, diverse rock types, strong heterogeneity, discontinuous gas reservoir distribution, and multiple controlling factors for gas and water distribution, making the selection of favorable development areas extremely difficult. This method is highly operable, conforms to the principles of sequence stratigraphy and sedimentology, and has been proven effective in evaluating and selecting favorable development areas for complex water-bearing gas reservoirs, laying a solid foundation for the development planning and production capacity construction of clastic gas reservoirs.

[0035] The present invention has other features and advantages, which will be apparent from or will be set forth in detail in the accompanying drawings and the following detailed description, which together serve to explain the particular principles of the invention. Attached Figure Description

[0036] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings.

[0037] Figure 1 This is a flowchart of a basin simulation stage data management method according to an embodiment of the present invention;

[0038] Figure 2 The results of high-frequency sequence division of the target layer in wells J1-J2-J3-J4-J5 in this embodiment of the invention are compared.

[0039] Figure 3 The embodiment of the present invention provides a comprehensive response model of seismic facies, logging facies, and lithofacies in the target stratigraphic segment.

[0040] Figure 4 The results of the lateral comparison of sedimentary microfacies in wells J1-J2-J3-J4-J5 in the target layer of this invention are presented in this embodiment.

[0041] Figure 5 The results of the depositional distribution characterization of the target layer in the embodiments of the present invention.

[0042] Figure 6 The results of the comparative analysis of the profiles of complex water-bearing gas reservoirs based on high-frequency sequence stratigraphy and sedimentary microfacies constraints in the embodiment of the present invention.

[0043] Figure 7The results of the planar gas-water distribution of the H12 sublayer, which is the objective layer of the present invention, are based on the combination of planar section and well-seismic combination, and are mutually constrained by the structure-lithology water-bearing gas reservoir.

[0044] Figure 8 The results of the planar gas-water distribution of the lithological water-bearing gas reservoir in the H11 sub-layer of the present invention are based on the combination of planar section and well-seismic combination, which are mutually constrained.

[0045] Figure 9 The results of the horizontal gas distribution of lithological water-bearing gas reservoirs are based on the combination of planar profile and well-seismic analysis, which are mutually constrained, in the embodiments of the present invention.

[0046] Figure 10 The objective of this invention is to determine the planar gas-water distribution characteristics of complex water-bearing gas reservoirs based on high-frequency sequence stratigraphy and sedimentary microfacies constraints.

[0047] Figure 11 The logging interpretation, reservoir evaluation, and lateral comparison results of wells J1-J2-J3-J4-J5 in the target formation of this invention are presented in this embodiment.

[0048] Figure 12 The results of the planar distribution evaluation of the gas-bearing reservoir in the target layer of this invention are presented in the embodiments of the present invention.

[0049] Figure 13 The results show the planar distribution of the thickness of the gas-bearing reservoir in the target layer of this invention.

[0050] Figure 14 The purpose of this invention is to evaluate the planar distribution results of the comprehensive selection area for the development of the target layer segment. Detailed Implementation

[0051] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, thereby enabling a full understanding of how the present invention uses technical means to solve technical problems and achieve technical effects, and allowing for implementation accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in each embodiment of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0052] This invention is primarily applied in the mid-to-late stages of oil and gas field development, during the comprehensive adjustment phase of reservoirs, and especially in the evaluation of remaining oil and gas reserves. In the mid-to-late stages of oil and gas field development, the distribution of remaining oil and gas becomes exceptionally complex due to the influence of different well types, such as multi-layered production in vertical wells and fracturing development in horizontal wells. This is particularly true given the strong geological heterogeneity and well-developed interlayers, which further affect oil and gas distribution. Whether the remaining oil and gas can achieve economic benefits needs to be evaluated. This embodiment, based on the high-frequency sequence stratigraphic framework and sedimentary microfacies constraints of braided river clastic rocks, combined with detailed reservoir logging interpretation and seismic attributes, conducts single-well reservoir evaluation. Furthermore, by combining the results of production capacity and economic evaluation, a development area selection evaluation standard is established, integrating well and seismic data to ultimately complete the method for selecting favorable development areas.

[0053] An embodiment of the present invention provides a method for evaluating the optimal selection of advantageous areas, the method comprising:

[0054] Step 1: Analyze the core and thin sections of the target layer to determine the lithology and rock type of the target layer, and analyze the sedimentary environment and sedimentary facies of the target layer in conjunction with the regional sedimentary background;

[0055] Step 2: Based on the analysis results of Step 1, establish the target layer high-frequency sequence lattice;

[0056] Step 3: Using the high-frequency stratigraphic framework, the target layer is divided into target sub-layers. Under the analysis constraints of the comprehensive response characteristics of well logging facies and seismic facies, the planar distribution of sedimentary microfacies with the target sub-layer as the unit is analyzed to determine the favorable lithological units of the gas reservoir.

[0057] Step 4: Based on the high-frequency sequence framework established in Step 2 and the planar distribution of sedimentary microfacies in Step 3, determine the favorable gas-bearing units in the favorable lithological units of the gas reservoir;

[0058] Step 5: Based on the favorable gas-bearing units determined in Step 4, evaluate and classify the reservoir physical property logging interpretation results of single wells according to the reservoir classification evaluation physical property standards, and list the reservoir classification evaluation type results in the well-connected sedimentary microfacies comparison, analyze the relationship between reservoir type and high-frequency sequence stratigraphy and sedimentary microfacies, and based on the constraints of the high-frequency sequence stratigraphy framework, combined with the lateral distribution characteristics of favorable sedimentary microfacies in reservoir development, complete the lateral comparison and planar distribution analysis of classified gas-bearing reservoirs, and determine the favorable gas-bearing physical property units;

[0059] Step 6: Based on the favorable gas-bearing physical property units, combine geology, gas reservoir engineering and economic evaluation to establish a selection evaluation standard for favorable gas reservoir areas, carry out the selection of favorable areas, and determine favorable development selection units.

[0060] In this embodiment, the favorable lithological unit refers to the favorable lithological unit for reservoir development determined by the sedimentary microfacies plane characterization results, which identifies the mid-shoal development zone as a favorable lithological unit for reservoir development.

[0061] In this embodiment, establishing the high-frequency sequence framework of the target layer includes: combining and calibrating the selected logging curves based on the analysis results of step 1 to obtain lithology-sensitive curves and their lithology-sensitive variation characteristics; using the lithology-sensitive variation characteristics of the lithology-sensitive curves to identify marker layers and high-frequency sequence interfaces, and to calibrate logging facies and seismic facies; and using the identification results and calibration results, establishing the high-frequency sequence framework of the target layer through well-seismic combination. Specifically, in this embodiment, obtaining the lithology-sensitive curves and their lithology-sensitive variation characteristics includes: selecting multiple logging curves, combining and calibrating the multiple logging curves based on the lithology analysis results of the core and thin sections, determining the response characteristics of various logging curves for different lithologies, and finding lithology-sensitive logging curves from the logging curve combinations as lithology-sensitive curves, and using the variation trend with lithology as lithology-sensitive variation characteristics.

[0062] In this embodiment, the method for obtaining the well-connected sedimentary micro-facies comparison includes: using the high-frequency sequence framework established in step 2 and the seismic facies response characteristics in step 3 as constraints for the lateral comparison of sedimentary microfacies, to complete the well-connected sedimentary micro-facies comparison of the target layer.

[0063] In this embodiment, step 4 includes: using reservoir fluid logging interpretation results, placing the logging fluid interpretation results in the well-connected sedimentary microfacies comparison; based on the high-frequency sequence framework established in step 2 and the sedimentary microfacies planar distribution described in step 3, drawing a gas reservoir profile using a combination of well and seismic analysis; analyzing the factors controlling gas and water distribution based on gas-water distribution characteristics; determining the gas-water distribution boundaries of gas-bearing units; and identifying favorable planar gas-bearing units. Specifically, determining the gas-water distribution boundaries of gas-bearing units includes: using the structural depth line corresponding to the gas layer and water layer boundary on a single well as the boundary; using the lithological boundary of the structurally low part of interconnected sand bodies under reservoir geophysical prediction constraints as the water layer boundary; and using the lithological boundary to determine the gas layer boundary at the structurally high part.

[0064] In this embodiment, step 4 further includes: using favorable gas-bearing units as constraints and well point gas thickness data as a basis, combining well and seismic data to complete the planar distribution of gas-bearing reservoir thickness.

[0065] Example 1

[0066] The invention is described below with reference to a specific example. Figure 1 To be continued Figure 14 .

[0067] like Figure 1As shown, this embodiment provides a method for analyzing major sedimentary characteristics and facies through detailed observation of cores and thin sections of the main target stratigraphic unit, identifying high-frequency sequence boundaries, calibrating logging curves, and combining well and seismic data to establish a high-frequency sequence framework. Under the constraints of the high-frequency sequence and guided by sedimentary understanding, and combined with geophysical properties reflecting lithology and sand body thickness distribution, favorable lithological units with favorable sedimentary microfacies development are determined. Based on reservoir and gas-bearing potential predictions, structural interpretation results, and gas layer distribution in gas reservoir profiles, favorable gas reservoir units are identified within the favorable lithological units. Based on reservoir evaluation results for the study area, reservoir evaluation is conducted on favorable gas-bearing units to determine the distribution of favorable gas-bearing physical property units. Finally, combining gas-bearing reservoir, production capacity, and economic evaluation results, as well as gas layer thickness distribution, evaluation criteria for selecting favorable areas are formulated, ultimately providing a highly operable method for selecting favorable development areas. The method includes the following steps:

[0068] (1) Detailed observation of the target layer cores and thin sections was conducted to determine the main lithology and rock types of the target layer. Combined with the regional sedimentary background, the sedimentary environment and sedimentary facies were analyzed. For example, the target layer of the clastic gas reservoir in the study area is about 60m thick. Detailed observation of the cores and thin sections of the cored section was conducted to determine the lithology and rock types. For example, the core sampling of well J3 in the target layer was relatively continuous. Based on detailed core observation and microscopic identification of thin sections, the overall core observation showed that it was mainly composed of gravelly coarse sandstone, coarse sandstone, and medium sandstone, with diverse bedding types, including trough cross-bedding, platy cross-bedding, scour surface structures, and other typical lithofacies of high-energy channels. The channel type of the main target layer, He 1 section, is mainly characterized by upward-shallowing meter-level sedimentary cycles, exhibiting an atypical binary structure. The thickness of the lower riverbed sediments is much greater than that of the upper embankment and overlying sediments, reflecting the characteristics of wide and shallow river bodies, rapid water flow, and unfixed and easily migrating channels. Comprehensive analysis suggests that it is a typical braided river deposit.

[0069] (2) Using core-logging cross-calibration, sensitive curves reflecting lithology were selected. Utilizing the logging response characteristics of high-frequency sequence interfaces, and combining well-logging and seismic analysis, high-frequency sequence interfaces were identified and compared across the entire well section under the constraint of the seismic interface, establishing a high-frequency sequence framework for the target layer. Using core-logging cross-calibration, natural gamma (GR) sensitive curves reflecting lithology were selected, and the three-porosity curves calculated for the tight layer were superimposed. Combined with shallow and deep resistivity curves, multiple curves were comprehensively used to determine sequence interfaces at various levels, identifying and comparing second- and third-order low-frequency sequence interfaces and fourth-order high-frequency sequence interfaces. Then, the lithological interfaces of the high-frequency sequence interfaces were further calibrated in detail using well-logging and seismic interfaces, with a full combination of well-logging and seismic analysis. Finally, a fourth-order high-frequency sequence was established, as shown in the results. Figure 2 .

[0070] (3) Based on steps (1) and (2), further identify and analyze sedimentary subfacies and microfacies markers based on core and thin section observations, finely calibrate well logging facies and seismic facies, establish the connection and comprehensive response model between lithofacies, well logging facies and seismic facies, and under the constraints of well logging facies and seismic facies, analyze the distribution of sedimentary microfacies to determine favorable gas reservoir lithological units.

[0071] Through lithofacies analysis of the main target layers in the study area in step (1), it is clear that the study area is dominated by braided river deposits. By calibrating well logging curves in detail through lithofacies analysis and combining core and well logging closely, vertical sequence analysis of braided river well logging facies was carried out. Overall, the vertical sequence is composed of sedimentary assemblages with increasingly finer grain size, which is consistent with the type of high-frequency sequence. It mainly includes the following two subfacies and three microfacies:

[0072] Floodplain subfacies: mainly developed in the upper part of the vertical facies sequence, with mudstone as the main lithology, interbedded with siltstone, and occasionally mudstone deformation bedding. The logging curves are low-amplitude, flat, and toothed, with low curve anomaly amplitude.

[0073] Channel subfacies: mainly developed in the middle and lower parts of the vertical facies sequence, with typical scour surfaces and various types of cross-bedding (gravelly) coarse sandstone facies, etc. The logging curves are highly serrated box-shaped with a small number of bell-shaped curves, including mid-shoal and channel-filling microfacies deposits.

[0074] Based on the analysis of petrology, sedimentary structures, and corresponding well logging responses of drill cores, as well as the seismic response characteristics calibrated by synthetic seismic records, well logging and seismic facies models of the main sedimentary microfacies of the Lower Shihezi Formation in the Shilijiahan area were established. Figure 3 Based on the above analysis results, guided by the upward finer sedimentary variation trend within the fourth-order high-frequency sequence, and based on the main sedimentary microfacies types observed in cores and thin sections, and under the constraints of sedimentary facies sequence regularity and well logging facies, single-well braided channel sedimentary subfacies and core bar, channel filling, and floodplain microfacies were delineated in the target interval based on the high-frequency sequence. Furthermore, the high-frequency sequence framework established in step (2) and the seismic facies response characteristics in step (3) were used as constraints for the lateral correlation of sedimentary microfacies. Figure 2 , Figure 3 ), to complete the correlation of sedimentary micro-connected wells in the target layer ( Figure 4 (a) and (b)). Figure 4 The well-connected seismic profiles corresponding to (a) and (b) in Figure (b) are shown. The lateral distribution of sedimentary microfacies in Figure (b) was completed under the attribute constraints of the seismic profile in Figure (a).

[0075] Based on single-well facies, interconnected-well facies, and facies sequence analysis, the seismic interpretation attribute of the maximum wave trough amplitude is selected as the constraint for sedimentary microfacies boundaries. Well-seismic analysis is combined and cross-calibrated. Guided by the sedimentary system and facies sequence rules, a planar microfacies diagram is compiled. Figure 5 Taking the plane phase of Box 1 as an example, the Jin 72 well area in the Shilijiahan area can be roughly divided into multiple composite channel zones from west to east.

[0076] (4) Using the reservoir fluid logging interpretation results, the logging fluid interpretation results are placed in the well-to-well sedimentary micro-relativity comparison. Based on the high-frequency sequence grid in step (2) and the sedimentary facies profile distribution in step (3), the gas reservoir profile is drawn by combining well and seismic logging, and all gas reservoir types in the study area are summarized. The factors controlling the gas-water distribution are analyzed, the gas-water distribution law is analyzed and summarized, and finally the favorable gas-bearing units are determined.

[0077] Using reservoir fluid logging interpretation results, these results are placed within a series of well-connected sedimentary micro-relativity comparisons. Constrained by high-frequency sequence stratigraphy and fine correlation of facies and sand bodies across well profiles, a study of the lateral distribution of gas and water within the study area is conducted to further summarize gas reservoir types and analyze the controlling factors of gas and water distribution. For example, analysis of single-well fluid interpretation results and fluid geophysical prediction results shows that the He1 section is a region of concentrated water layer development in the north and west of the study area, a region of concentrated gas layer and gas-water co-development in the south, and a region of coexistence of gas-water layers and gas-water co-development in the central area. For instance, the lateral distribution of gas and water in the Jin116-J72P2-Jin9 wells within the Jin72 well area, a region with overall water layer development, is examined... Figure 6 In the middle (b) section, vertically, gas and water co-occur in the same layer, and gas-bearing layers are usually developed in the upper part of relatively continuous sand bodies. Laterally, they are usually developed in the higher structural parts of relatively continuous sand bodies, exhibiting the characteristics of gas above and water below, which is a relatively typical structural-lithological gas reservoir. From the lateral distribution of gas layers in the southern part of the Jin 72 well area (Figure 6(a)), the gas layers are mostly laterally pinch-out type, the main target layer is basically water-free, and the distribution of gas layers is not completely controlled by the structural high parts. Therefore, it is mainly characterized by lithological gas reservoirs. The middle part is mainly a transitional type from structural-lithological gas reservoirs to pure lithological gas reservoirs, that is, water-bearing lithological gas reservoirs affected by microstructures.

[0078] Based on the longitudinal and lateral distribution of gas and water layers in single wells and interconnected wells, guided by the gas-water distribution controlled by different gas reservoir types, and taking structural interpretation, geophysical reservoir, and fluid prediction results as important references, this study combines the results of planar sedimentary microfacies and lithological unit division to determine the gas-water distribution boundaries of different gas-bearing units for different gas reservoir types. Specifically, for the structural-lithological gas reservoirs in the northern part of the study area, the gas-water boundaries of interconnected gas reservoir units are primarily determined by the structural depth line corresponding to the gas and water layer boundaries in a single well. Under the constraints of reservoir geophysical prediction, the lithological boundaries of interconnected sand bodies at structurally low positions are mainly (gas-bearing) water layer boundaries, while at structurally high positions, lithological boundaries are used to determine the gas layer boundaries. Figure 7 ). Figure 7This method is for determining the gas-water boundary of tectonic-lithologic gas reservoirs. It combines the maximum trough amplitude attribute to guide the analysis of sedimentary microfacies distribution, identifying favorable core-shoal lithologic units. Further, it integrates the gas reservoir profile (two cross and longitudinal sections), gas-bearing prediction results, and tectonic interpretation results, comprehensively considering the lithologic boundary and the tectonic gas-water distribution boundary to determine the gas reservoir boundary of the tectonic-lithologic gas reservoir. Figure (e) shows the gas level distribution map; the other figures ((a), (b), (c), (d), and (f)) are references used to determine the gas level distribution in this figure. For determining the gas-water boundary of the water-bearing lithologic gas reservoir in the central part of the study area, it seeks the boundaries of interconnected lithologic bodies, appropriately considering the influence of microstructures and reservoir properties on water layer distribution within these bodies. Figure 8 These six figures are for determining the gas level distribution in water-bearing lithologic gas reservoirs, taking into account various factors and... Figure 7 Similarly, by combining the maximum wave trough amplitude attribute to guide the analysis of constrained sedimentary microfacies distribution, favorable lithological units of the core bar zone are identified. Further, by combining the gas reservoir profile (two cross and longitudinal profiles) and gas-bearing prediction results, and comprehensively considering the lithological boundary, the gas reservoir boundary of the water-bearing lithologic gas reservoir is determined. Figure (e) shows the gas level distribution map; the other figures ((a), (b), (c), (d), and (f)) are references used to determine the gas level distribution in this figure. However, the gas level distribution of this type of gas reservoir lacks a unified gas-water interface and has a low dependence on structural isolines. For the water-free pure lithologic gas reservoirs in the southern part of the study area, the gas reservoir boundary is mainly determined based on the lithological boundary. Figure 9 These six figures are for determining the planar distribution of gas reservoirs in water-free lithologic gas reservoirs, taking into account factors and... Figure 7 Similarly, by combining the maximum wave trough amplitude attribute to guide the analysis of constrained sedimentary microfacies distribution, favorable core-bar lithological units are identified. Further, by combining gas reservoir profiles (two cross and longitudinal profiles), with a focus on lithological boundaries, the gas reservoir boundaries of the lithological gas reservoirs are determined. Gas-bearing prediction results are only used as an auxiliary reference. Figure (e) shows the gas level distribution map; the other figures ((a), (b), (c), (d), and (f)) are reference data used to determine the gas level distribution in this figure. Through the above methods, the gas level distribution of the main target layers is compiled in detail, ultimately determining the different interconnected gas-bearing units (…). Figure 10 ). Figure 10 (a) shows the planar prediction results of reservoir gas content. Figure 10 (b) is for Figure 7 , Figure 8 and Figure 9 Different gas reservoir types, combined Figure 10 (a) The result of the gas-water distribution plane characterization in the whole region.

[0079] (5) According to the physical property standards for reservoir classification and evaluation, the logging interpretation results of single-well reservoir physical properties are evaluated and classified. Based on the constraints of the four-level high-frequency sequence framework and reservoir prediction results, and combined with the lateral distribution characteristics of favorable sedimentary microfacies in reservoir development, the planar distribution analysis of classified reservoirs in lateral comparison and gas-bearing reservoir evaluation is completed.

[0080] Detailed reservoir logging interpretation was conducted on dozens of completed wells in the study area. Reservoirs were classified according to the reservoir classification evaluation criteria: Class I reservoirs (porosity ≥ 12.5%), Class II reservoirs (porosity ≥ 9% to < 12.5%), and Class III reservoirs (porosity ≥ 5.5% to < 9%). Taking well J3 in the study area as an example, four reservoir layers were interpreted in the target interval, with a total thickness of 21.6 m. Two of these were Class II reservoirs, with a cumulative thickness of 10 m, and individual layer thicknesses ranging from 1.5 m to 8.5 m, averaging 5 m. Two of these were Class III reservoirs, with a cumulative thickness of 11.6 m, and individual layer thicknesses ranging from 2 m to 9.6 m, averaging 5.8 m.

[0081] The reservoir classification and evaluation results are listed in the well-connected sedimentary micro-comparison ( Figure 4 As can be seen, the distribution of reservoir types in single wells and interconnected wells is complex and highly heterogeneous. However, further detailed observation reveals that the distribution of different reservoir types is closely related to their location and sedimentary microfacies within high-frequency sequence stratigraphy, such as... Figure 4 As shown, within the fourth-order high-frequency sequence, the sedimentary microfacies consist of a progressively finer sequence from bottom to top, consisting of channel mid-shoals, channel infill, and floodplain microfacies. Reservoirs with good physical properties are typically located in the lower part of the high-frequency sequence. Physical properties deteriorate upwards, thus forming multiple superimposed combinations of increasingly poor physical properties within the target interval.

[0082] Since the target layer in the study area is a braided river deposit, the number of fourth-order high-frequency sequences within the target layer is the same, and the thickness difference is small, indicating that the high-frequency sequences have good vertical and horizontal correlation in the study area. Using the fourth-order high-frequency sequences as correlation markers for constraint, and combining the lateral distribution characteristics of sedimentary microfacies favorable for reservoir development such as mid-channel bars and channel filling, a one-to-one correlation method was adopted to finally complete the reservoir evaluation and correlation profiles for the entire well network. Figure 11 The results showed that in the target stratigraphic interval of the study area, the reservoirs were mainly of type II and III, with relatively few type I reservoirs. The different types of reservoirs exhibited a characteristic of "thin interbedded layers." Figure 11 The first and second-class high-quality reservoirs are generally developed within the core-shoal sedimentary microfacies in the lower part of the fourth-order high-frequency sequence.

[0083] Based on the evaluation and comparison of single-well and interconnected-well reservoirs and the gas horizontal plane distribution, and constrained by the fourth-order high-frequency sequence stratigraphy framework, combined with the favorable sedimentary microfacies planar distribution characteristics of reservoir development, the planar distribution of gas-bearing reservoirs is completed, and favorable gas-bearing physical property units are determined. Figure 12 ).

[0084] (6) Combine geology, gas reservoir engineering and economic evaluation to establish evaluation standards for the selection of favorable gas reservoir areas, carry out the selection of favorable areas, and determine favorable development selection units.

[0085] Based on the above geological, logging, and seismic studies, and constrained by the favorable gas-bearing units determined in step (4) of the gas horizontal plane distribution analysis, and using wellpoint gas thickness data as a basis, the gas-bearing reservoir thickness planar distribution was completed through a combination of well and seismic analysis. Figure 13 Based on the comprehensive evaluation map of gas-bearing reservoirs in each of the above-mentioned layers and the production capacity evaluation of single wells, and with reference to the economic development boundary, the selection evaluation criteria for the study area are established, as shown in Table 1.

[0086] Table 1

[0087]

[0088] The areas are divided into two types of favorable development areas. The first type is areas where profitable development has been proven under current economic conditions. These areas have a cumulative reservoir thickness of 6-8m or more, or a cumulative reservoir thickness of 12-16m or more, with horizontal well flow rates of 60,000-80,000 cubic meters per day or more. These areas are considered to have relatively secure production capacity. The second type is areas where profitable development is predicted under current economic conditions. These areas are mainly based on multiple factors, including adjacent well reservoir evaluation, reservoir geophysical prediction (thickness and physical properties, etc.), and structural interpretation. The reservoir and gas content prediction results are similar to or better than these areas, and the structural location is roughly the same as or higher than these areas. Category II favorable development areas are those that cannot be economically developed under current economic conditions, but could potentially be effectively developed if gas prices rise, engineering processes improve, technologies advance, and costs decrease. These areas include those with a cumulative thickness of 4-6m or more for Category I reservoirs, or 8-12m or more for Category II reservoirs, with current horizontal well flow rates exceeding 40,000-60,000 cubic meters per day. Also included are areas more than 1km away from confirmed Category II wells, but with seismic prediction attributes similar to or better than Category II wells, and with contiguous sandstone structures at the same or higher elevations. These are all Category II favorable development areas, also known as secondary economic development areas. The final development site selection evaluation results for the study area are as follows: Figure 14 As shown.

[0089] The above technical solution is merely one embodiment of the present invention. For those skilled in the art, based on the application methods and principles disclosed in this invention, various types of modifications can be easily made, and it is not limited to the development zone classification boundaries chosen in the above specific embodiment, which use horizontal well unobstructed flow rates of 60,000-80,000 cubic meters / day and 40,000-60,000 cubic meters / day. Different development zone evaluation standards can be selected according to actual circumstances. Therefore, the development zone evaluation standards selected above are a preferred method for classifying favorable development areas based on regional economic productivity evaluation results, and are not restrictive.

[0090] This embodiment addresses the challenges of selecting favorable development areas in complex, water-bearing, low-permeability clastic gas reservoirs due to rapid vertical and horizontal variations, diverse rock types, strong heterogeneity, discontinuous gas reservoir distribution, and complex gas-water distribution control factors. Through comprehensive geological research and combined with reservoir engineering production capacity and economic evaluation results, an evaluation standard for selecting favorable development areas is established, ultimately providing a highly operable method for this purpose. Specifically, based on high-frequency sequence stratigraphic constraints and reservoir correlation evaluation results, combined with actual tested production capacity and economic evaluation, an evaluation standard for selecting favorable areas is established. This method combines well and seismic analysis to ultimately select favorable development areas. It solves the problem of the difficulty in selecting favorable target areas for complex, water-bearing, low-permeability clastic gas reservoirs during the exploration and development stage due to complex lithology, highly heterogeneous thin interbedded reservoir properties, and complex gas-water distribution patterns, providing a decision-making basis for the efficient development of gas fields.

[0091] Example 2

[0092] This disclosure also provides an electronic device, which includes:

[0093] At least one processor; and,

[0094] A memory that is communicatively connected to at least one processor; wherein,

[0095] The memory stores instructions that can be executed by at least one processor, which enables the at least one processor to perform the aforementioned advantageous area selection evaluation method.

[0096] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0097] This 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, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0098] The processor may be a central processing unit (CPU) or other form of processing unit with 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 this disclosure, the processor is used to execute computer-readable instructions stored in the memory.

[0099] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0100] Example 3

[0101] This disclosure provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the aforementioned advantageous area selection evaluation method.

[0102] A computer-readable storage medium according to embodiments of the present disclosure stores non-transitory computer-readable instructions. When these non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods described in the foregoing embodiments of the present disclosure are performed.

[0103] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0104] Example 4

[0105] This disclosure provides an advantageous area selection evaluation apparatus. The apparatus includes:

[0106] The target layer sedimentation module is used to analyze the core and thin sections of the target layer, determine the lithology and rock type of the target layer, and analyze the sedimentary environment and sedimentary facies of the target layer in combination with the regional sedimentary background.

[0107] A high-frequency layer sequence grid module, wherein the high-frequency layer sequence grid is used to establish a high-frequency layer sequence grid for the target layer;

[0108] Favorable lithological unit module, which is used to divide the target layer into target sublayers using the high-frequency stratigraphic framework, and under the analysis constraints of the comprehensive response characteristics of well logging facies and seismic facies, analyze the planar distribution of sedimentary microfacies with the target sublayer as the unit, and determine the favorable lithological unit of the gas reservoir;

[0109] A favorable gas-containing unit module, wherein the favorable gas-containing unit is used to determine favorable gas-containing units;

[0110] The favorable gas-bearing physical property module is used to evaluate and classify the logging interpretation results of single-well reservoir physical properties according to the physical property standards for reservoir classification and evaluation, and to list the reservoir classification and evaluation type results in the well-connected sedimentary micro-facies comparison. It analyzes the relationship between reservoir type and high-frequency sequence stratigraphy and sedimentary microfacies. Based on the constraints of the high-frequency sequence stratigraphy framework and combined with the lateral distribution characteristics of favorable sedimentary microfacies in reservoir development, it completes the lateral comparison and planar distribution analysis of classified gas-bearing reservoirs and determines favorable gas-bearing physical property units.

[0111] The favorable development area selection module is used to combine geology, gas reservoir engineering and economic evaluation based on the favorable gas-bearing physical property units, establish the evaluation criteria for the selection of favorable gas reservoir areas, carry out the selection of favorable areas, and determine favorable development area selection units.

[0112] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they 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 optimal selection of advantageous areas, characterized in that, include: Step 1: Analyze the core and thin sections of the target layer to determine the lithology and rock type of the target layer, and analyze the sedimentary environment and sedimentary facies of the target layer in conjunction with the regional sedimentary background; Step 2: Based on the analysis results of Step 1, establish the target layer high-frequency sequence lattice; Step 3: Using the high-frequency stratigraphic framework, the target layer is divided into target sub-layers. Under the analysis constraints of the comprehensive response characteristics of well logging facies and seismic facies, the planar distribution of sedimentary microfacies with the target sub-layer as the unit is analyzed to determine the favorable lithological units of the gas reservoir. Step 4: Based on the high-frequency sequence framework established in Step 2 and the planar distribution of sedimentary microfacies described in Step 3, determine the favorable gas-bearing units in the favorable lithological units of the gas reservoir; Step 5: Based on the favorable gas-bearing units determined in Step 4, evaluate and classify the reservoir physical property logging interpretation results of single wells according to the reservoir classification evaluation physical property standards, and list the reservoir classification evaluation type results in the well-to-well sedimentary microfacies comparison, analyze the relationship between reservoir type and high-frequency sequence stratigraphy and sedimentary microfacies, and based on the constraints of the high-frequency sequence stratigraphy framework, combined with the lateral distribution characteristics of favorable sedimentary microfacies in reservoir development, complete the lateral comparison and planar distribution analysis of classified gas-bearing reservoirs, thereby determining favorable gas-bearing physical property units; Step 6: Based on the favorable gas-bearing physical property units, combine geology, gas reservoir engineering and economic evaluation to establish a selection evaluation standard for favorable gas reservoir areas, carry out the selection of favorable areas, and determine favorable development selection units.

2. The method for evaluating the optimal selection of advantageous areas according to claim 1, characterized in that, The establishment of the high-frequency sequence framework for the target layer includes: combining and calibrating the selected logging curves based on the analysis results of step 1 to obtain lithology-sensitive curves and their lithology-sensitive variation characteristics; using the lithology-sensitive variation characteristics of the lithology-sensitive curves to identify marker layers and high-frequency sequence interfaces, and to calibrate logging facies and seismic facies; and using the identification results and the calibration results, establishing the high-frequency sequence framework for the target layer through a combination of well and seismic analysis.

3. The method for evaluating the optimal selection of advantageous areas according to claim 2, characterized in that, Obtaining lithology-sensitive curves and their lithology-sensitive variation characteristics includes: selecting multiple logging curves, combining and calibrating the multiple logging curves based on the lithology analysis results of the core and thin sections, determining the response characteristics of various logging curves for different lithologies, finding logging curves that are sensitive to lithology from the logging curve combinations as lithology-sensitive curves, and taking the variation trend with lithology as lithology-sensitive variation characteristics.

4. The method for evaluating the optimal selection of advantageous areas according to claim 1, characterized in that, The method for obtaining the well-connected sedimentary micro-facies comparison includes: using the high-frequency sequence framework established in step 2 and the seismic facies response characteristics in step 3 as constraints for the lateral comparison of sedimentary microfacies, to complete the well-connected sedimentary micro-facies comparison of the target layer.

5. The method for evaluating the optimal selection of advantageous areas according to claim 1, characterized in that, Step 4 includes: using the reservoir fluid logging interpretation results, listing the logging fluid interpretation results in the well-connected sedimentary microfacies comparison, and drawing the gas reservoir profile by combining well and seismic analysis based on the high-frequency sequence grid established in step 2 and the sedimentary microfacies planar distribution in step 3. According to the gas-water distribution characteristics, the factors controlling the gas-water distribution are analyzed, the gas-water distribution boundary of the gas-bearing unit is determined, and the favorable planar gas-bearing unit is determined.

6. The method for evaluating the optimal selection of advantageous areas according to claim 5, characterized in that, The determination of the gas-water distribution boundary of the gas-bearing unit includes: taking the structural depth line corresponding to the gas layer and water layer boundary on a single well as the boundary, the lithological boundary of the interconnected sand bodies under the constraints of reservoir geomorphological prediction as the water layer boundary, and using the lithological boundary to determine the gas layer boundary in the structural high part.

7. The method for evaluating the optimal selection of advantageous areas according to claim 1, characterized in that, Step 4 further includes: using favorable gas-bearing units as constraints and well point gas thickness data as a basis, combining well and seismic data to complete the planar distribution of gas-bearing reservoir thickness.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the advantageous area selection evaluation method according to any one of claims 1-7.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing a computer to perform the advantageous area selection evaluation method according to any one of claims 1-6.

10. A device for evaluating the optimal selection of advantageous areas, characterized in that, include: The target layer sedimentation module is used to analyze the core and thin sections of the target layer, determine the lithology and rock type of the target layer, and analyze the sedimentary environment and sedimentary facies of the target layer in combination with the regional sedimentary background. A high-frequency layer sequence grid module, wherein the high-frequency layer sequence grid is used to establish a high-frequency layer sequence grid for the target layer; Favorable lithological unit module, which is used to divide the target layer into target sublayers using the high-frequency stratigraphic framework, and under the analysis constraints of the comprehensive response characteristics of well logging facies and seismic facies, analyze the planar distribution of sedimentary microfacies with the target sublayer as the unit, and determine the favorable lithological unit of the gas reservoir; A favorable gas-containing unit module, wherein the favorable gas-containing unit is used to determine favorable gas-containing units; The favorable gas-bearing physical property module is used to evaluate and classify the logging interpretation results of single-well reservoir physical properties according to the physical property standards for reservoir classification and evaluation, and to list the reservoir classification and evaluation type results in the well-connected sedimentary micro-facies comparison. It analyzes the relationship between reservoir type and high-frequency sequence stratigraphy and sedimentary microfacies. Based on the constraints of the high-frequency sequence stratigraphy framework and combined with the lateral distribution characteristics of favorable sedimentary microfacies in reservoir development, it completes the lateral comparison and planar distribution analysis of classified gas-bearing reservoirs, thereby determining favorable gas-bearing physical property units. The favorable development area selection module is used to combine geology, gas reservoir engineering and economic evaluation based on the favorable gas-bearing physical property units, establish the evaluation criteria for the selection of favorable gas reservoir areas, carry out the selection of favorable areas, and determine favorable development area selection units.

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