Method for preferably selecting shale gas structure storage favorable area not based on formation pressure

Abstract

The invention provides a method for preferably selecting a shale gas structure storage favorable area not based on formation pressure. The method comprises the steps that a target research area is selected, and a core exploration target layer series is determined; on the basis of a target stratum shale gas preservation mechanism, core parameters independent of stratum pressure data are screened, and a comprehensive evaluation index system containing target stratum self-sealing performance, regional cover stratum conditions and structural transformation action parameters is constructed; spatial distribution analysis is carried out on each parameter, grading is carried out according to geological laws and adjacent region experience, and weight coefficients are distributed according to the influence degree of the parameters on storage conditions; obtaining a comprehensive score of the structure storage condition of each evaluation unit through grade assignment and weighted stacking calculation; and delineating a shale gas structure storage favorable area according to the comprehensive score. The method is suitable for low-exploration-degree areas with complex structures, sparse drilling wells or lack of formation pressure data, and has the advantages of objective evaluation, high operability and high practical value.

Description

Technical Field

[0001] This application relates to the field of shale gas exploration technology, and in particular to a method for selecting favorable shale gas structural preservation zones without relying on formation pressure. Background Technology

[0002] Shale gas, as a clean and efficient unconventional natural gas resource, has become a key focus of global energy exploration and development. Especially in the southern marine strata, Cambrian and Permian marine shale formations possess enormous exploration potential due to their high organic matter abundance, suitable thermal evolution, and wide distribution. However, compared to commercially developed strata such as the Silurian Longmaxi Formation, large-scale breakthroughs in the exploration of new marine shale gas strata have not yet been achieved. The core bottleneck lies in the complex tectonic preservation conditions. Most target areas have undergone multiple phases of tectonic movement, with significant effects such as ancient uplift, fault development, and stratigraphic erosion, leading to easy escape of shale gas and making the identification of effective reservoir areas extremely difficult.

[0003] Traditional assessments of shale gas structural preservation conditions heavily rely on formation pressure data (such as pressure coefficients and overpressure levels), considering abnormally high pressure as the core indicator of effective gas sequestration. However, in actual exploration, low-exploration areas (such as the edges of ancient uplifts and the periphery of basins) generally suffer from sparse drilling and limited geophysical data coverage, making it difficult to obtain continuous and reliable formation pressure data. Furthermore, formation pressure is dynamically influenced by multiple factors such as tectonic activity and fluid migration; using it solely as an evaluation criterion fails to reveal the deep-seated control mechanisms of preservation conditions and easily obscures favorable zones with stable local structures and well-developed caprocks. While existing multi-factor evaluation methods attempt to incorporate parameters such as fracture density and caprock thickness, they suffer from problems such as scattered parameter selection, lack of geological adaptability in grading standards, and subjective weight allocation. This makes it difficult to establish a standardized evaluation process applicable to complex structural areas and independent of formation pressure, thus hindering the efficiency of strategic site selection for marine shale gas in low-exploration areas. Summary of the Invention

[0004] In view of this, the embodiments of this application provide a method for selecting favorable shale gas structural preservation areas without relying on formation pressure. This method is applicable to marine shale gas exploration in areas with well-developed ancient uplift edges or faults. It has the advantages of objective evaluation, strong operability, and high practical value, and can provide reliable technical support for the deployment of shale gas exploration target areas.

[0005] The technical solution of this application embodiment is implemented as follows: In a first aspect, embodiments of this application provide a method for selecting favorable shale gas structural preservation zones without relying on formation pressure, the method comprising: Select target study areas with shale gas exploration potential and determine the core exploration target stratigraphic units; Based on the shale gas preservation mechanism of the target strata, parameters that do not depend on formation pressure data and can reflect the core influencing factors of the preservation conditions of the target strata are selected. A comprehensive evaluation index system is constructed that includes at least the self-sealing parameters of the target strata, the regional caprock condition parameters, and the tectonic modification parameters, so that the index system matches the geological background of the evaluation area and the characteristics of the target strata. For each parameter in the constructed multi-factor evaluation index system, spatial distribution analysis was carried out, and based on the geological characteristics of the evaluation area and the exploration experience of neighboring areas, a grading standard was preset to divide each parameter into multiple levels, which serves as a standardized parameter level basis for subsequent quantitative calculations. Weighting coefficients are assigned based on the degree of influence of each parameter on shale gas preservation conditions; A fixed score is assigned to each of the divided levels. The scores of each parameter level obtained in each evaluation unit are multiplied by the corresponding weight coefficients and then summed to obtain the comprehensive score of the construction preservation conditions of that unit. Based on the comprehensive scoring results, favorable areas for shale gas structural preservation were delineated.

[0006] Secondly, embodiments of this application also provide an apparatus for selecting favorable shale gas structural preservation zones without relying on formation pressure, the apparatus comprising: The selection module is used to select target study areas with shale gas exploration potential and determine the core exploration target stratigraphic units; The module is used to screen parameters that do not depend on formation pressure data and can reflect the core influencing factors of the preservation conditions of the target layer based on the shale gas preservation mechanism of the target layer. It constructs a comprehensive evaluation index system that includes at least the self-sealing parameters of the target layer, the regional caprock condition parameters, and the tectonic modification parameters, so that the index system matches the geological background of the evaluation area and the characteristics of the target layer. The partitioning module is used to conduct spatial distribution analysis on each parameter in the constructed multi-factor evaluation index system, and to pre-determine the grading standards based on the geological laws of the evaluation area and the exploration experience of neighboring areas, dividing each parameter into multiple levels, which provides a standardized parameter level basis for subsequent quantitative calculations. The allocation module is used to assign weight coefficients based on the degree of influence of each parameter on shale gas preservation conditions. The calculation module is used to assign fixed scores to each level of the division. It multiplies the scores of each parameter level obtained in each evaluation unit with the corresponding weight coefficients and then sums them to obtain the comprehensive score of the construction and preservation conditions of the unit. The determination module is used to delineate favorable areas for shale gas structural preservation based on the comprehensive scoring results.

[0007] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the method described in any of the first aspects for selecting favorable shale gas structural preservation areas without relying on formation pressure.

[0008] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the method described in any one of the first aspects for selecting favorable shale gas structural preservation zones without relying on formation pressure.

[0009] The embodiments of this application have the following beneficial effects: By constructing a multi-factor system that specifically covers the self-enclosure of the target layer, regional caprock conditions, and tectonic alteration, the reliance on formation pressure data is completely eliminated, effectively solving the evaluation challenges in low-exploration areas with complex structures, sparse drilling, or lack of pressure data. Secondly, through a quantitative process of parameter classification, weight allocation, and weighted superposition, combined with the final delineation of favorable areas based on the structural characteristics of the evaluation region, the subjectivity of traditional qualitative evaluation is avoided, and the optimal results are ensured to fit the actual geological background. This significantly improves the objectivity, repeatability, and accuracy of the evaluation, enabling rapid focus on high-preservation-potential target areas. It provides efficient and reliable technical support for shale gas exploration deployment in low-exploration areas, significantly reducing exploration costs and risks. Attached Figure Description

[0010] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating steps S101-S106 provided in the embodiments of this application; Figure 2 This is a schematic diagram of the device provided in this application embodiment that does not select favorable shale gas structural preservation areas based on formation pressure; Figure 3 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0013] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0014] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0015] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0016] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application and is not intended to limit this application.

[0018] See Figure 1 , Figure 1This is a flowchart illustrating steps S101-S106 of the method for selecting favorable shale gas structural preservation zones without relying on formation pressure, as provided in the embodiments of this application. Figure 1 Steps S101-S106 shown will be explained.

[0019] In step S101, a target study area with shale gas exploration potential is selected, and the core exploration target stratigraphic sequence is determined.

[0020] This step is a fundamental prerequisite for the implementation of this application's embodiments, aiming to clarify the spatial scope and core target strata for shale gas exploration. In practice, it is necessary to combine regional geological survey results, existing exploration well data, and geophysical exploration data (such as gravity, electrical, and seismic data) to select areas with clear tectonic backgrounds, stable target strata development, and shale gas exploration potential as evaluation areas. Simultaneously, based on key shale gas accumulation indicators such as stratigraphy, organic matter abundance, and thermal evolution, specific target strata (such as the Cambrian Niutitang Formation and the Permian Longtan Formation, etc., marine shale strata) are identified to ensure that subsequent evaluations focus on the core exploration targets and avoid reduced evaluation efficiency or result deviations due to ambiguous targets. For example, in this application's embodiments, combined with the geological characteristics of the southwestern margin of the Xuefeng Uplift, the Majiang Uplift and its surrounding areas are identified as the evaluation area, with the Cambrian Niutitang Formation shale as the target strata, laying a clear target foundation for subsequent multi-factor evaluations.

[0021] In step S102, based on the shale gas preservation mechanism of the target stratum, parameters that do not depend on formation pressure data and can reflect the core influencing factors of the preservation conditions of the target stratum are selected. A comprehensive evaluation index system is constructed that includes at least the self-sealing parameters of the target stratum, the regional caprock condition parameters, and the tectonic modification parameters, so that the index system matches the geological background of the evaluation area and the characteristics of the target stratum.

[0022] Here, a comprehensive evaluation index system is formed by systematically screening parameters that do not rely on formation pressure data and have a key controlling effect on shale gas structural preservation conditions. From the perspective of shale gas preservation mechanisms, the self-sealing property of the target layer is the intrinsic basis for gas sequestration (e.g., burial depth determines formation pressure sequestration capacity), regional caprock conditions are the external barrier for gas escape (e.g., the thickness of the direct caprock affects vertical sealing), and tectonic alteration is the main external factor that disrupts preservation conditions (e.g., fractures lead to gas leakage, and formation attitude affects lateral diffusion). Therefore, the index system must include at least these three types of parameters.

[0023] Specifically, the target layer burial depth is selected as the self-sealing parameter because it directly affects the formation temperature, pressure environment, and rock density. Too shallow a burial depth (e.g., ≤1000m) easily leads to formation pressure release, fracture opening, and a high risk of gas escape; a moderate burial depth (e.g., 1500-2000m) is conducive to forming a stable storage environment. The direct caprock thickness is selected as the regional caprock condition parameter because, as the caprock immediately above the target layer, a thicker direct caprock has lower porosity and permeability, resulting in a stronger vertical capping capacity for shale gas in the target layer (e.g., a thickness ≥250m significantly better than a caprock ≤150m). The parameters for tectonic alteration include fault distribution density, distance from basement faults, distance from the target stratum outcrop, and stratigraphic attitude / structural style. This is because faults are the main pathway for shale gas escape (higher fault density and closer proximity to basement faults lead to greater stratigraphic fragmentation and easier destruction of the storage system). The target stratum outcrop is the direct outlet for gas escape along the bedding plane (closer to the outcrop, higher escape risk). Stratigraphic attitude (such as dip angle) affects the efficiency of lateral gas diffusion (the larger the dip angle, the stronger the diffusion effect dominated by lateral permeability, and the easier it is for gas to escape). By constructing this multi-factor index system, we can comprehensively cover the "internal foundation-external barrier-destructive factors" of shale gas preservation, avoiding the one-sidedness of traditional single-factor evaluation.

[0024] In step S103, spatial distribution analysis is carried out on each parameter in the constructed multi-factor evaluation index system, and a grading standard is preset based on the geological laws of the evaluation area and the exploration experience of neighboring areas to divide each parameter into multiple levels, which serve as a standardized parameter level basis for subsequent quantitative calculations.

[0025] Here, by integrating multi-source data, spatial characterization and hierarchical classification of various parameters are performed, providing a standardized basis for subsequent weighted overlay. Geological survey data includes 1:200,000 regional geological maps, field outcrop profile measurement data, and well core analysis data, which can be used to determine the outcrop distribution of the target layer, measured values ​​of stratigraphic attitude, and lithological characteristics of the caprock. Geophysical exploration data covers gravity, electrical resistivity, and seismic data. Seismic data, after static correction, denoising, and overlay migration processing, can be used for target layer depth inversion, fault identification, and stratigraphic attitude interpretation (e.g., calculating the apparent dip angle of the stratigraphy from the reflection axis dip angle of the seismic profile). Gravity data, after topographic correction and Bouguer correction, can extract residual gravity anomalies to assist in the division of tectonic units and the location of basement faults. Electrical resistivity data (e.g., magnetotelluric (MT)) can obtain resistivity profiles through Robust inversion, identifying low-resistivity fault anomalies and high-resistivity stable blocks in the basement, providing data support for the calculation of parameters such as fault distribution density and distance from basement faults.

[0026] Based on spatial distribution analysis, a grading standard needs to be developed according to geological patterns and exploration experience in adjacent areas, classifying each parameter into different levels (e.g., Levels I, II, III, and IV) to intuitively reflect the impact of parameters on preservation conditions. The grading process must adhere to the principle of "adapting to local conditions." For example, the grading of fault distribution density should be combined with the fault development background of the evaluation area; in tectonically stable areas (e.g., the core of ancient uplifts), ≤0.3 km / km 2 The formation can be classified into Class I (good stratigraphic integrity), while in areas with dense faults (such as basin edges), the threshold needs to be adjusted appropriately to conform to the actual geological conditions. Simultaneously, the classification standard must be operable to ensure accurate classification based on existing data. For example, the depth of the target layer can be directly correlated with the classification interval through seismic data inversion results, avoiding the problem of strong subjectivity in classification due to ambiguous standards. In this embodiment, by integrating two-dimensional seismic survey lines (2300 depth points), residual gravity anomaly data, and field outcrop measurement data, the spatial distribution of parameters such as the depth and fault distribution density of the Niutitang Formation was completed. Based on the Cambrian shale gas preservation patterns, each parameter was classified into Class I-IV, providing a clear classification basis for subsequent quantitative evaluation.

[0027] In step S104, weighting coefficients are assigned according to the degree of influence of each parameter on shale gas preservation conditions.

[0028] Because the control effects of various parameters on preservation conditions differ significantly, weighting coefficients need to be determined through scientific methods. The expert experience method can rely on the understanding of regional tectonic background and shale gas accumulation patterns by senior geological exploration experts to judge the relative importance of each parameter (e.g., long-term activity of basement faults has the strongest destructive effect on the preservation system, and its weight should be higher than other parameters). The neighboring area comparison method can refer to the parameter impact analysis results of areas where shale gas has been commercially developed (e.g., the Longmaxi Formation of the Silurian in the Sichuan Basin), and adjust the weights based on the geological similarity between the evaluation area and neighboring areas. The statistical analysis method can determine the weight allocation by conducting correlation analysis on the preservation conditions and parameter data of existing exploration wells, quantifying the degree of correlation between parameters and preservation effects (e.g., gas saturation, test gas production).

[0029] Regardless of the method used, it is essential to ensure that the sum of the weight coefficients of all parameters is 1.0, and that the weight allocation conforms to geological logic. For example, in this application, the weight of the distance from the basement fault is set to 0.3 (the highest) because basement faults (such as the F1 and F2 faults in the embodiments) deeply incise the basement, are active over a long period, and easily penetrate the target layer and caprock, forming permanent gas escape channels. Their destructive effect on preservation conditions is far greater than that of other parameters. The weight of the apparent dip angle is set to 0.25 (the second highest) because the lateral permeability of shale is significantly higher than its vertical permeability. The larger the dip angle, the higher the efficiency of gas diffusion and escape along the strata, thus having a greater impact on the preservation of gas in shallow and medium-depth shale. The impact of fault distribution density is second only to that of basement faults. The weights of fault distribution density (0.2), target layer burial depth (0.15), and distance from the target layer outcrop (0.1) decrease sequentially, corresponding to their decreasing influence on preservation conditions. Fault distribution density reflects the overall fragmentation of the regional strata, with a wide range of influence, but local compensation can be achieved through caprock. The target layer burial depth is a self-sealing foundation, but its influence on preservation is weaker than that of faults and attitude due to tectonic uplift. The influence of distance from the outcrop is mainly concentrated in the shallow part of the surface, with relatively local constraints on the preservation of the middle and deep layers. Reasonable weight allocation ensures that each parameter can reflect its actual control role in the comprehensive evaluation, improving the scientificity and accuracy of the evaluation results.

[0030] In step S105, a fixed score is assigned to each of the divided levels. The scores of each parameter level obtained in each evaluation unit are multiplied by the corresponding weight coefficients and then summed to obtain the comprehensive score of the construction preservation conditions of the unit.

[0031] Here, through quantitative assignment and weighted summation, the differences in the levels of each parameter are transformed into an intuitive comprehensive score, achieving a quantitative representation of preservation conditions. First, fixed scores are assigned to different levels of each parameter. The score setting must reflect the differences in quality between levels and maintain a unified quantitative standard—in this application, the assignment method of Level I = 1.0, Level II = 0.75, Level III = 0.5, and Level IV = 0.25 is used because this assignment system can clearly distinguish the differences between different levels (the difference between adjacent levels is 0.25) and conforms to the progressive relationship of "excellent-good-average-poor," avoiding distortion of evaluation results due to unreasonable score intervals. For example, Level I (excellent) corresponds to 1.0 points, representing that the parameter is completely beneficial to preservation conditions; Level IV (poor) corresponds to 0.25 points, representing that the parameter is severely detrimental to preservation conditions, and intermediate levels decrease proportionally, ensuring that the score is positively correlated with the degree of quality of preservation conditions.

[0032] Based on the assigned values, a weighted summation method is used to calculate the comprehensive score, with the formula "Comprehensive Score = Σ (Parameter Weight × Parameter Level Score)". This calculation method combines the influence (weight) of each parameter with its actual performance (level score), achieving an organic integration of multiple factors. For example, in the evaluation of a grid unit (107°45′E, 26°30′N) in the central part of the Jidong anticline in this application embodiment, the Niutitang Formation has a burial depth of 1800m (Level II, 0.75 points, weight 0.15), a fault distribution density of 0.2km / km² (Level I, 1.0 point, weight 0.2), a distance of 2.2km from the basement fault (Level I, 1.0 point, weight 0.3), and a distance of 4.5km from the outcrop of the target layer (Level I, 1.0 point, weight 0.3). 1) The apparent dip angle of the strata is 7° (Level I, 1.0 point, weight 0.25). The calculated comprehensive score is 0.15×0.75+0.2×1.0+0.3×1.0+0.1×1.0+0.25×1.0=0.9625 points. This high score directly reflects that all parameters in this area are favorable for preservation conditions, indicating high overall preservation potential. In contrast, a certain grid unit in the eastern part of the Majiang Gentle Syncline has all parameters at Level IV, resulting in a comprehensive score of only 0.25 points, clearly indicating poor preservation conditions. This calculation method can transform complex multi-factor evaluations into concise numerical results, providing clear quantitative basis for subsequent delineation of favorable areas.

[0033] In step S106, favorable areas for shale gas structure preservation are delineated based on the comprehensive scoring results.

[0034] Here, by analyzing the spatial distribution characteristics of the comprehensive scores, advantageous areas for shale gas structural preservation are identified, providing target area guidance for exploration deployment. In practice, it is necessary to first draw a spatial distribution map of the comprehensive scores based on the comprehensive scores of each evaluation unit (e.g., a 1km×1km grid unit) using a geographic information system (e.g., ArcGIS), visually presenting the distribution pattern of high and low scores. Subsequently, combined with the regional tectonic background, geophysical anomaly characteristics (e.g., high resistivity stable blocks, exclusion of low residual gravity anomaly areas), and geological knowledge, the threshold for classifying favorable areas is determined. Generally, areas with the highest comprehensive scores and structural stability are classified as Class I favorable areas (core target areas), areas with the next highest scores and relatively stable structures are classified as Class II favorable areas (potential target areas), and areas with scores below the threshold are considered unfavorable areas.

[0035] The determination of the threshold should follow the principle of "geological rationality + exploration practicality": on the one hand, it is necessary to ensure that the high-scoring area matches the geologically favorable conditions such as structurally stable units (e.g., the core of anticlines, the footwall of thrust faults), and areas with well-developed caprocks, to avoid misjudgment due to ignoring the geological background based solely on the score; on the other hand, it is necessary to combine exploration needs to ensure that the area of ​​the Class I favorable area is moderate and the target is clear, so as to facilitate the subsequent deployment of parameter wells or 3D seismic exploration. For example, in the embodiment of this application, combined with the comprehensive score distribution (0.25-0.98) and structural stability analysis, the threshold of the Class I favorable area was determined to be a comprehensive score ≥0.7 and located in a structurally stable unit, and finally the central part of the Jidong anticline (area 180 km²) was delineated. 2 (Score 0.82-0.98) and the western side of the Majiang gentle syncline (area 55km²) 2 Two Class I favorable areas (scoring 0.70-0.81) were identified, and geophysical constraints such as seismic reflection characteristics and resistivity anomalies were used to verify their effectiveness. Unfavorable areas, such as water-rich fractured zones and basement fractured zones, were eliminated, ensuring the favorable areas possess practical exploration value. The final identified favorable areas can serve as key target areas for the next stage of exploration. For example, parameter wells can be prioritized in Class I favorable areas to verify gas content, while further geophysical exploration can be conducted in Class II favorable areas to refine structural features, significantly improving the targeting and success rate of shale gas exploration.

[0036] In some embodiments, the target layer self-sealing parameter includes the target layer burial depth, the regional cap layer condition parameter includes the direct cap layer thickness, and the tectonic modification parameter includes at least three of the following: fault distribution density, distance from basement faults, distance from the surface outcrop of the target layer, and stratigraphic attitude / structural style.

[0037] The burial depth of the target layer is a core parameter reflecting its self-sealing properties. Its selection is based on the intrinsic mechanism of shale gas preservation: as the burial depth increases, the pressure from the overlying strata increases, and the porosity and permeability of the rocks decrease, forming a denser reservoir environment, which is conducive to the adsorption and storage of shale gas. At the same time, the increased burial depth is accompanied by an increase in formation temperature. Although this will affect the thermal evolution of organic matter, within a reasonable burial depth range (e.g., 1500-3000m), a favorable environment for hydrocarbon accumulation can be formed with synergistic temperature and pressure. Conversely, when the burial depth is too shallow (e.g., ≤1000m), the overlying pressure is insufficient, the rock density is low, and it is easily affected by surface weathering and erosion, resulting in the development of fractures and causing a large amount of shale gas to escape. When the burial depth is too deep (e.g., >4000m), although a high-pressure environment may be formed, the formation rocks are prone to plastic deformation, and the drilling cost increases significantly, which is not conducive to actual exploration and development. Therefore, selecting the burial depth of the target layer as the self-sealing parameter of the target layer can directly quantify the sealing capacity of the target layer itself, providing key intrinsic indicator support for evaluation.

[0038] The thickness of the direct caprock, which is the immediate layer above the target shale layer, is a key factor determining its vertical sealing capacity, thus becoming a core evaluation parameter for regional caprock conditions. From a sealing mechanism perspective, the direct caprock needs to possess lithological characteristics of low porosity and low permeability (such as mudstone and gypsum), while its thickness directly affects its sealing stability and effectiveness. Greater thickness results in better lateral continuity of the caprock, effectively preventing the upward escape of shale gas from the target layer. Simultaneously, a thicker caprock can better buffer the damage to the caprock system caused by tectonic activity, reducing the risk of caprock failure due to localized fracture development. For example, when the direct caprock thickness is ≥250m, its vertical permeability can typically be maintained at 10. -15 m 2 The following capping capabilities are significantly superior to capping layers with a thickness of ≤150 μm (permeability easily reaches 10). -14 m 2 (Above); In the embodiments of this application, the thickness of the direct caprock (Palang Formation) of the Cambrian Niutitang Formation is generally >300m, providing a stable vertical cap for the shale gas in the target layer. However, the thickness of the caprock in the eastern part of the Majiang Gentle Syncline drops to 280-300m. Although it still has good capping capacity, the difference in the impact of thickness on the capping effect is evident. Therefore, selecting the thickness of the direct caprock as a regional caprock condition parameter can accurately reflect the strength of the capping barrier above the target layer and is an important external indicator for evaluating shale gas preservation conditions.

[0039] Tectonic alteration is a major external factor that disrupts shale gas preservation conditions. Its impact is multi-dimensional and complex, therefore, it is necessary to select multiple parameters for comprehensive characterization, including at least three of the following: fault distribution density, distance from basement faults, distance from the surface outcrop of the target layer, and stratigraphic attitude / tectonic style. The specific selection logic is as follows: Fractures are the main pathway for shale gas escape. The fracture density (total fracture length per unit area) directly reflects the degree of fragmentation of the regional strata. The higher the density, the worse the strata integrity, the more developed the fracture network, and the higher the risk of vertical and lateral escape of shale gas from the target layer through fractures. For example, a fracture density ≤ 0.3 km / km 2 In areas such as the core of the Kidong anticline, the strata are generally intact, and faults cause minimal damage to the preserved system; while the density is >0.7 km / km 2 In areas such as the eastern part of the Majiang Syncline, between faults F1 and F4, dense fault development and severe strata fracturing make it almost impossible to effectively store shale gas. Therefore, fault density can quantify the overall intensity of regional tectonic disruption and is a fundamental parameter for evaluating tectonic alteration.

[0040] Basement faults, as deep, long-term active faults that cut deep into the basement (such as the F1 boundary slope fault and the F2 venting fault in this embodiment), exhibit activity intensity far greater than shallow faults. They not only directly penetrate the target layer and caprock, forming permanent escape channels, but also induce changes in the stress field of surrounding strata, leading to the development of secondary fractures and further damaging preservation conditions. The closer to the basement fault, the stronger the impact of its activity and the worse the preservation conditions. For example, in areas ≤0.5 km from the basement fault, the strata are significantly dragged and compressed by the fault, resulting in severe rock fracturing and complete failure of the caprock system; while in areas ≥1.5 km away, the impact of the fault is weak, and the preservation system is relatively stable. Therefore, the distance from the basement fault can accurately characterize the degree of damage to local preservation conditions caused by deep faults and is a key parameter for distinguishing between high-risk and low-risk tectonic zones.

[0041] The surface outcrop of the target layer is a direct window for shale gas to connect with the atmosphere. Driven by groundwater flow and gas concentration gradients, shale gas from the target layer will diffuse along the bedding planes towards the outcrop, forming an "escape channel." The closer to the outcrop, the shorter the gas escape path, the higher the escape efficiency, and the worse the preservation conditions. For example, in areas ≤1.0 km from the outcrop, the gas has almost completely escaped, and the gas content of the target layer is extremely low; while in areas ≥3.0 km away, the escape path is long and the loss is large, which is conducive to gas preservation. In the embodiments of this application, the Niutitang Formation is exposed on the surface in the eastern part of the Majiang gentle syncline, and the surrounding 1 km range is a Class IV preservation area, which fully demonstrates the influence of the outcrop on preservation conditions. Therefore, the distance from the surface outcrop of the target layer can effectively evaluate the risk of gas escape caused by surface erosion and is an important parameter for characterizing shallow tectonic alteration.

[0042] The stratigraphic attitude (primarily referring to the dip angle) directly affects the lateral diffusion efficiency of shale gas. The lateral permeability of shale (typically 0.1-1 mD) is much higher than its vertical permeability (typically 0.001-0.01 mD). The larger the dip angle, the faster the gas diffuses laterally along the bedding plane under the influence of gravity and concentration gradients, resulting in a higher risk of escape. For example, in gently dipping areas with a dip angle of 0°-10° (such as the core of the Jidong anticline), lateral diffusion is weak, and gas is easily enriched; while in steeply dipping areas with a dip angle >20° (such as the footwall of the F2 fault on the eastern wing of the Jidong anticline), lateral diffusion is strong, making gas difficult to preserve. Simultaneously, structural types (such as anticlines, synclines, and thrust-nappes) also affect preservation conditions. The compacted strata in the core of anticlines are conducive to preservation; the footwall of thrust-nappes is subjected to pressure from the overlying strata, improving capping conditions. Therefore, stratigraphic attitude / structural type can quantify the influence of structural morphology on gas diffusion and preservation, and is an important dimension for evaluating tectonic alteration.

[0043] In summary, at least three of the above-mentioned parameters should be selected for tectonic modification. These parameters can be flexibly combined according to the tectonic characteristics of the evaluation area (e.g., in areas with developed faults, focus on fault distribution density and distance from basement faults; in areas with developed outcrops, focus on distance from the surface outcrop of the target layer and stratigraphic attitude). This ensures comprehensive coverage of the ways in which tectonic modification damages preservation conditions and avoids biased evaluation due to missing parameters.

[0044] In some embodiments, the spatial distribution analysis of each evaluation parameter is performed and classified into four levels: I, II, III, and IV. The classification standard for the burial depth of the target layer is as follows: ≥2000m is Class I, 1500–2000m is Class II, 1000–1500m is Class III, and ≤1000m is Class IV. The classification standard for the thickness of the direct cap layer is as follows: ≥250m is Class I, 200–250m is Class II, 150–200m is Class III, and ≤150m is Class IV. The grading standard for the fracture distribution density is: ≤0.3km / km 2 Class I, 0.3–0.5 km / km 2 Class II, 0.5–0.7 km / km 2 Class III, >0.7km / km 2 Class IV; The classification criteria for the distance from the basement fracture are as follows: ≥1.5km is Class I, 1.0–1.5km is Class II, 0.5–1.0km is Class III, and ≤0.5km is Class IV. The classification criteria for the distance from the surface outcrop of the target layer are as follows: ≥3.0km is Class I, 2.0–3.0km is Class II, 1.0–2.0km is Class III, and ≤1.0km is Class IV; The classification criteria for the stratigraphic attitude / structural style are as follows: 0°–10° is Class I, 10°–15° is Class II, 15°–20° is Class III, and >20° is Class IV.

[0045] The four-level classification system (I (Excellent), II (Good), III (Average), and IV (Poor)) is based on the accuracy requirements and geological principles for evaluating shale gas preservation conditions. This system clearly distinguishes the impact of different parameters on the quality of preservation conditions while avoiding the ambiguity caused by too many classifications or the insufficient precision caused by too few. In practical application, the four-level classification accurately corresponds to the geological condition gradient of "completely favorable - fairly favorable - fairly unfavorable - completely unfavorable," for example, a fault distribution density ≤ 0.3 km / km². 2 (Class I) represents intact and undamaged strata, representing a completely favorable preservation environment; while >0.7km / km 2(Class IV) represents severely fractured strata, representing a completely unfavorable preservation environment. Classes II and III, on the other hand, form a smooth transitional gradient, accurately capturing the subtle differences in parameter variations affecting preservation conditions. Furthermore, this grading method, along with subsequent grade assignments (e.g., Class I 1.0 point, Class II 0.75 point), forms a matching quantitative system, directly translating parameter grade differences into calculable score differences. This provides clear foundational data for comprehensive scoring and avoids distorted evaluation results due to inappropriate grading methods.

[0046] The burial depth of the target layer directly controls the formation pressure environment and rock density, and is the core factor determining the self-sealing capability of the target layer. ≥2000m is classified as Class I because within this depth range, the overlying strata pressure is sufficient to allow shale to form a tight reservoir (porosity typically ≤5%), and the formation temperature can meet the requirements for organic matter pyrolysis and hydrocarbon generation, creating a stable gas storage environment. 1500–2000m (Class II) is slightly shallower, but still maintains good storage capacity, with only a slight risk of pressure release in some areas. Below 1000–1500m (Class III), the overlying pressure is insufficient, rock density decreases, the probability of fracture opening increases, and the risk of gas escape significantly increases. ≤1000m (Class IV) is too shallow, easily affected by surface weathering and erosion, formation pressure is basically released, and fractures are densely developed, making effective gas storage difficult. This classification standard is highly consistent with marine shale gas exploration practices. For example, in the exploration of the Niutitang Formation shale in the Cambrian, the gas saturation in areas with a burial depth ≥2000m is generally >40%, while the gas saturation in areas ≤1000m is mostly <10%, which verifies the rationality of the classification standard.

[0047] As the immediate caprock above the target layer, its thickness directly determines its vertical sealing capacity. The greater the thickness, the lower the porosity and permeability, and the stronger the vertical blocking effect on shale gas in the target layer. Caprocks ≥250m are classified as Class I because the vertical permeability of caprocks of this thickness (such as mudstone and gypsum) is typically <10. -15 m 2 It can effectively block gas from escaping upwards, forming a permanent cap; the cap layer thickness is slightly reduced at 200–250m (Class II), but it still has good capping capacity, and local capping failure may only occur in areas of intense tectonic activity; the cap layer thickness is insufficient at 150–200m (Class III), and the vertical permeability is prone to increase to 10. -14 m 2In the above-mentioned cases, the sealing capacity is significantly weakened, and gas easily escapes vertically along the pores of the caprock. Caprock thickness ≤150m (Class IV) is too thin to form an effective seal, and uneven thickness may even create "windows," leading to complete gas escape from the target layer. For example, in the embodiments of this application, in areas where the direct caprock (Cambrian Palang Formation) thickness ≥250m, the shale gas preservation conditions of the target layer are excellent, while in areas with a local thickness ≤150m, no effective gas-bearing indications were found, confirming the scientific validity of this classification standard.

[0048] Fractures are the main pathway for shale gas escape, and the fracture density (total fracture length per unit area) directly reflects the degree of fragmentation of the regional strata. (≤0.3 km / km) 2 It is classified as Category I because at this density, the fracture spacing is large (usually >3 km), the overall stratigraphic continuity is good, the damage of fractures to the preservation system is negligible, and gas is unlikely to escape through fractures; 0.3–0.5 km / km 2 (Type II) At this density, small local fractures exist, but no fracture network has formed, limiting the impact on preservation conditions; 0.5–0.7 km / km 2 At (Type III) densities, the fracture spacing decreases to 1.5–2 km, forming a semi-continuous fracture network. Gas in the target layer can locally escape through these fractures, significantly deteriorating preservation conditions; >0.7 km / km 2 At density levels of (Class IV), fractures are densely developed, forming a complete fracture network. Gas from the target layer can rapidly escape through multiple fractures, making effective storage virtually impossible. This standard is consistent with exploration experience in adjacent areas (such as the periphery of the Huangling Uplift), where the fracture distribution density is ≤0.3 km / km. 2 In areas where the test gas yield is generally >10×10 4 m 3 / d, while >0.7km / km 2 In the tested areas, the air was mostly dry, which verified the accuracy of the grading threshold.

[0049] Basement faults are deep, long-term active faults that cut deep into the basement. Their activity not only directly penetrates the target and caprocks, forming permanent escape channels, but also triggers changes in the stress field of surrounding strata, leading to the development of secondary fractures. ≥1.5km is classified as Class I because beyond this distance, the influence of basement fault activity has largely disappeared, the strata stress is stable, no secondary fractures have developed, and the preservation system remains intact. Within 1.0–1.5km (Class II), the weak influence of basement fault activity may result in a small number of localized secondary fractures, but these do not damage the overall preservation system. Within 0.5–1.0km (Class III), the influence of basement faults is significantly enhanced, secondary fractures develop densely, the caprock's sealing capacity is compromised, and the risk of gas escape from the target strata is high. Within ≤0.5km (Class IV), the strata are directly dragged and compressed by basement faults, resulting in severe rock fracturing, with both the caprock and target strata being penetrated by the faults, and the preservation system completely failing. For example, in the embodiments of this application, the target layer of shale gas has good gas content in the middle part of the Jidong anticline ≥1.5km away from the base fault (F2 Shidongkou fault), while the target layer near the fault zone ≤0.5km away has been weathered and eroded, which verifies the practical significance of the classification standard.

[0050] The surface outcrop of the target layer is the direct window for gas to connect with the atmosphere. Gas can diffuse along the strata towards the outcrop. The closer to the outcrop, the shorter the diffusion path and the higher the efficiency. ≥3.0 km is classified as Class I because at this distance, the gas diffusion path is long and losses are significant, allowing for effective enrichment within the target layer. Within 2.0–3.0 km (Class II), the diffusion path shortens, and local gas concentrations may decrease, but some gas-bearing potential remains. Within 1.0–2.0 km (Class III), the diffusion risk increases significantly, and most of the gas in the target layer has already diffused, resulting in a substantial decrease in gas saturation. Within ≤1.0 km (Class IV), gas can rapidly diffuse along the strata to the surface, and the target layer is essentially gas-free. In the embodiments of this application, the target layer in the eastern part of the Shiban Syncline, which is ≥3.0km from the Niutitang Formation outcrop, shows obvious gas content, while in the eastern part of the Majiang Gentle Syncline, which is ≤1.0km from the outcrop, only a small amount of residual organic matter is found in the target layer, with no signs of gas content, which fully confirms the rationality of the classification standard.

[0051] The stratigraphic attitude (mainly referring to the dip angle) directly affects the lateral diffusion efficiency of shale gas. The lateral permeability of shale (0.1–1 mD) is much higher than the vertical permeability (0.001–0.01 mD). The larger the dip angle, the faster the lateral diffusion rate of gas. 0°–10° is classified as Class I because the strata are gentle at this dip angle, the lateral diffusion is weak, and gas is easily enriched in the target layer. At a dip angle of 10°–15° (Class II), the lateral diffusion is slightly enhanced, but the impact on gas enrichment is limited. At a dip angle of 15°–20° (Class III), the lateral diffusion efficiency is significantly improved, and gas easily diffuses and escapes along the bedding plane, reducing the gas-bearing area. At a dip angle >20° (Class IV), the lateral diffusion is strong, and gas is difficult to stay in the target layer, making it basically impossible to form effective enrichment. For example, the core strata of the Jidong anticline have a dip angle of 3°–8° (Class I), and the target strata have uniform and full gas content. However, the eastern wing of the anticline has a dip angle of 20°–28° (Class IV), and the target strata have poor gas content. This verifies the matching of the classification standard with the actual geological conditions.

[0052] In summary, the four-level grading method and core parameter grading standards not only follow the inherent mechanism of shale gas preservation but also combine practical exploration experience, ensuring the scientific nature, accuracy, and operability of single-factor evaluation. This provides standardized basic data for subsequent multi-factor comprehensive scoring and avoids evaluation result deviations caused by ambiguous or unreasonable grading standards. It is the key technical support for this method to accurately select favorable areas for shale gas structural preservation.

[0053] In some embodiments, the weighting coefficients are allocated as follows: distance from the basement fault is 0.3, stratigraphic attitude is 0.25, fault distribution density is 0.2, target layer burial depth is 0.15, and distance from the target layer surface outcrop is 0.1.

[0054] The weighting coefficients reflect the relative importance of each evaluation parameter to shale gas preservation conditions. Due to differences in geological background (such as tectonic activity intensity and caprock development), data availability, and exploration stages in different evaluation areas, multiple determination methods are needed to meet the requirements of different scenarios and ensure the rationality and flexibility of weight allocation. The expert experience method is applicable to low-exploration areas with complex geological backgrounds and limited existing exploration data. It relies on the professional knowledge and practical experience of senior shale gas geological exploration experts to determine the importance of each parameter. Experts need to comprehensively consider the structural characteristics of the evaluation area (such as whether it is a fault-developed zone), the characteristics of the target layer (such as burial depth and caprock thickness), and the core constraints on shale gas preservation to determine the weight and priority of each parameter. For example, in the edge area of ​​a fault-developed paleo-uplift (as in the embodiment of this application), experts, based on experience, believe that the basement faults have the strongest destructive effect on preservation conditions (highest weight), followed by the stratigraphic attitude (affecting lateral diffusion), then the fault distribution density (overall degree of fragmentation), and finally the burial depth of the target layer and its distance from the outcrop. Based on this, the weight coefficients are determined as follows: distance from basement fault 0.3, stratigraphic attitude 0.25, fault distribution density 0.2, target layer burial depth 0.15, and distance from the target layer surface outcrop 0.1.

[0055] The advantage of the expert experience method lies in its ability to quickly determine weights by combining regional geological characteristics, avoiding evaluation stagnation due to insufficient data. However, to reduce subjectivity, it is usually necessary to organize 3-5 experts to score independently, and use the average or weighted average method to determine the final weights to ensure the objectivity of the results. For example, in this application, three experts scored separately, and the weights assigned to the distance from the basement fault were 0.28, 0.3, and 0.32, respectively. The final average was taken as 0.3, which improved the reliability of the weight allocation.

[0056] The neighboring area comparison method is applicable to evaluation areas with similar geological backgrounds and where shale gas preservation conditions have been evaluated. It determines the weighting coefficients of the evaluation area by comparing the influence of various parameters in neighboring areas on preservation effects (such as gas saturation and test gas production). In practice, it is necessary to first screen neighboring areas with similar tectonic backgrounds (e.g., both being paleo-uplift margins), target stratigraphic systems (e.g., both being Cambrian shale), and hydrocarbon accumulation conditions (e.g., organic matter abundance and thermal evolution) to the evaluation area; then, obtain the weighting distribution results of each parameter in the neighboring areas and the corresponding exploration verification results (e.g., whether areas controlled by high-weight parameters are favorable areas); finally, considering the subtle differences between the evaluation area and neighboring areas (e.g., fault activity intensity and caprock lithology), fine-tune the weights of the neighboring areas to obtain the weighting coefficients for the evaluation area.

[0057] For example, in the Cambrian shale gas evaluation around the Huangling Uplift in this application embodiment, the weight of distance from the basement fault is 0.28, and the weight of stratigraphic attitude is 0.26. Considering that the intensity of basement fault activity in this area is slightly lower than that in the neighboring area, but the lateral diffusion of stratigraphy is more significant, the weight of distance from the basement fault is adjusted to 0.3, and the weight of stratigraphic attitude is adjusted to 0.25, while the weights of other parameters remain consistent with those in the neighboring area. The advantage of the neighboring area comparison method is that it relies on existing practical results, has high reliability in weight allocation, and can reduce the evaluation cycle, especially suitable for areas with low exploration levels and lack of local data.

[0058] Statistical analysis is applicable to medium-to-high exploration areas where a certain number of exploration wells (e.g., more than 10) already exist and measured data and preservation effects (e.g., gas content test data) for each parameter are available. Weighting coefficients are determined by quantitatively analyzing the correlation between each parameter and the preservation effect. Specific steps include: first, collecting parameter data (e.g., target layer depth, fracture distribution density) and preservation effect indicators (e.g., gas saturation, pressure coefficient) for each exploration well; then, using statistical methods such as correlation analysis (e.g., Pearson correlation coefficient), regression analysis (e.g., multiple linear regression), or principal component analysis, calculating the contribution of each parameter to the preservation effect (e.g., the larger the absolute value of the regression coefficient, the higher the contribution); finally, standardizing the contributions (the sum of the contributions of all parameters is 1.0) to obtain the weighting coefficients for each parameter.

[0059] For example, in a certain exploration area, multiple linear regression analysis revealed that the regression coefficient between the distance to the basement fault and gas saturation was 0.32, the stratigraphic attitude was 0.27, the fault distribution density was 0.21, the target layer depth was 0.16, and the distance to the surface outcrop of the target layer was 0.04. After standardization, the weighting coefficients were 0.32, 0.27, 0.21, 0.16, and 0.04, respectively, consistent with geological understanding. The advantage of statistical analysis lies in its complete data-driven approach, offering the strongest objectivity and scientific rigor in weight allocation, effectively avoiding interference from subjective factors, and making it suitable for areas with abundant data.

[0060] In some embodiments, the grade values ​​are assigned as follows: Grade I = 1.0, Grade II = 0.75, Grade III = 0.5, and Grade IV = 0.25. The comprehensive score is calculated using a weighted summation method.

[0061] Grade I (Excellent) is assigned a value of 1.0, Grade II (Good) 0.75, Grade III (Average) 0.5, and Grade IV (Poor) 0.25. The score difference between adjacent grades is fixed at 0.25. This difference can significantly distinguish the degree of excellence of different grades, while avoiding insufficient evaluation accuracy due to excessively large differences (such as 0.5) or unclear grade distinction due to excessively small differences (such as 0.1). For example, in the evaluation of the burial depth of the target layer, Grade I (≥2000m) is assigned a value of 1.0, which means that the burial depth conditions are completely favorable for preservation, and Grade IV (≤1000m) is assigned a value of 0.25, which means that the burial depth conditions are severely unfavorable for preservation. The intermediate Grades II and III decrease by 0.25, clearly corresponding to the transitional state of "Good-Average", so that the score difference is directly linked to the difference in actual geological conditions.

[0062] If a non-uniform difference is used (e.g., 1.0 for Level I, 0.8 for Level II, 0.5 for Level III, and 0.2 for Level IV), the degree of difference between adjacent levels will be inconsistent (difference between Level II and Level I is 0.2, and between Level III and Level II is 0.3). This can easily lead to the evaluation results being overly sensitive or insensitive to the differences between certain levels. For example, in the comprehensive score calculation, the 0.2 difference between Level II and Level I might be amplified or reduced by the weight, potentially masking subtle differences in actual storage conditions or exaggerating irrelevant differences, thus affecting the accuracy of the evaluation. Therefore, a fixed difference of 0.25 between adjacent levels ensures that the differences in quality between each level are reflected evenly and accurately during the quantification process.

[0063] The scoring criteria must be consistent with the geological logic of shale gas preservation conditions; that is, the higher the score, the more favorable the corresponding parameter is to preservation conditions. A score of 1.0 for Level I indicates that the parameter is in the most favorable state for preservation (e.g., fault distribution density ≤ 0.3 km / km²). 2 The strata are intact and undamaged; a Class II parameter of 0.75 is favorable for preservation, but there are slight unfavorable factors (such as a fault distribution density of 0.3-0.5 km / km). 2 The stratigraphic integrity is relatively good, but there are local minor faults; the Class III representative parameter of 0.5 has a balanced effect on preservation, but there are obvious unfavorable factors (such as fault distribution density of 0.5-0.7 km / km). 2 The stratigraphic integrity is poor, and faults cause some damage to preservation; a Class IV representative parameter of 0.25 is severely unfavorable for preservation, making it almost impossible to form effective preservation (e.g., fault distribution density > 0.7 km / km). 2 The strata are severely fractured, and a large amount of gas has escaped.

[0064] This scoring system aligns with geological understanding. For example, in this embodiment, the apparent dip angle of a certain grid unit in the central part of the Jidong anticline is 7° (Level I, 1.0 point), indicating that the strata in this area are gently sloping with weak lateral diffusion, which is highly favorable for preservation. In contrast, the apparent dip angle of a certain grid unit in the eastern part of the Majiang syncline is 22° (Level IV, 0.25 point), indicating that the strata in this area are steeply dipping with strong lateral diffusion, which is severely unfavorable for preservation. The difference in scores accurately reflects the difference in preservation potential under actual geological conditions. Furthermore, this scoring standard is simple and intuitive, facilitating practical operation. Evaluators only need to determine the parameter level to directly correspond to a fixed score, without additional calculation or adjustment, thus improving the operability of the method.

[0065] The weighted summation method is the most commonly used and scientific calculation method in multi-factor comprehensive evaluation. Its core logic is "parameter importance (weight) × parameter actual performance (grade score)". By accumulating the scores, a comprehensive score is obtained, which can objectively reflect the comprehensive impact of each parameter on preservation conditions. The weighted summation method combines the weight (importance) of each parameter with the grade score (actual performance), highlighting the influence of key parameters (such as the high-weight distance from the basement fault, whose grade score contributes more to the comprehensive score) while also taking into account the role of other parameters, avoiding extreme evaluation results due to the excellence or poorness of a single parameter. For example, if the distance from the basement fault of an evaluation unit is level I (1.0 point, weight 0.3), but the fault distribution density is level IV (0.25 points, weight 0.2), the comprehensive score of this unit will reflect the actual situation of "small impact of basement faults but fragmented strata" through weighted summation calculation, rather than the result being determined by only one parameter.

[0066] In this embodiment, the Niutitang Formation in a grid unit in the middle of the Jidong anticline has a burial depth of Level II (0.75 points, weight 0.15), which is not optimal. However, other parameters (fracture distribution density, distance from the basement fracture, etc.) are all Level I (1.0 points). After weighted summation, the comprehensive score is 0.9625 points, which accurately reflects the actual situation of the unit: "Although the burial depth is slightly shallow, other conditions are excellent, and the overall preservation conditions are good." If the simple summation method is used (without considering weights), the comprehensive score is 0.75+1.0+1.0+1.0+1.0=4.75 points, which cannot reflect the differences in importance of each parameter. Moreover, the scoring range of different units is not uniform (e.g., the simple summation range of 5 parameters is 1.25-5.0), making it difficult to make horizontal comparisons. The weighted summation method has a fixed scoring range (0.25-1.0), which is more convenient for the threshold division of favorable areas.

[0067] The weighted summation method's calculation formula (Comprehensive Score = Σ(Parameter Weight × Parameter Level Score)) is simple and intuitive, requiring no complex mathematical models or algorithms. Evaluators can easily understand the calculation process and clearly explain the composition of the comprehensive score. By decomposing the comprehensive score, the contribution of each parameter to the final result can be clearly identified, facilitating subsequent analysis of the dominant factors in favorable or unfavorable areas. For example, if an unfavorable area has a comprehensive score of 0.35, decomposition reveals that the main reasons are: distance from the basement fault is level IV (0.25 points, weight 0.3, contribution 0.075 points) and stratigraphic attitude is level IV (0.25 points, weight 0.25, contribution 0.0625 points). Based on this, targeted exploration recommendations such as "avoiding basement fault zones and selecting gently sloping strata" can be proposed.

[0068] In this embodiment, the comprehensive score calculated by the weighted summation method accurately distinguishes the differences in preservation conditions in different areas. The score for Class I favorable areas (central part of the Jidong anticline) is 0.82-0.98, the score for Class II favorable areas (western side of the Majiang syncline) is 0.70-0.81, and the score for unfavorable areas is <0.6. The scoring gradient is clear and completely consistent with geological understanding. Furthermore, by decomposing the score, the advantageous parameters of each favorable area can be clearly identified (such as the fault distribution density and stratigraphic orientation advantage in the central part of the Jidong anticline), providing clear directional guidance for subsequent exploration deployment.

[0069] In summary, the grading standards of Level I = 1.0, Level II = 0.75, Level III = 0.5, and Level IV = 0.25, combined with the weighted summation method for comprehensive scoring, ensure the quantification, accuracy, and operability of multi-factor evaluation. This allows the comprehensive score to objectively and intuitively reflect the quality of shale gas structural preservation conditions, providing a reliable quantitative basis for the final delineation of favorable areas.

[0070] In some embodiments, geophysical exploration data includes at least two combinations of gravity, electrical, and seismic data, which are preprocessed for structural analysis and parameter inversion.

[0071] Gravity, electrical resistivity, and seismic data reflect the characteristics of underground geological structures from different dimensions, each with its own advantages and applicable scope. Selecting at least two types of data in combination can achieve data complementarity, improve the accuracy of structural analysis and parameter inversion, and avoid the limitations of single data.

[0072] Gravity data primarily reflects the distribution differences of rock layers with varying densities underground. Gravity anomalies (especially residual gravity anomalies) can be used to identify basement undulations, tectonic unit boundaries, and fault zone locations, providing a foundation for analyzing the tectonic framework of the evaluation area. For example, high-density basement blocks (such as granite) produce positive gravity anomalies, while low-density sedimentary basins produce negative gravity anomalies. By analyzing the distribution of high and low residual gravity anomalies, tectonic units such as anticlines and synclines can be delineated (e.g., in the embodiments of this application, the Jidong anticline corresponds to a high residual gravity anomaly area, and the Majiang gentle syncline corresponds to a low residual gravity anomaly area). Simultaneously, due to significant differences in stratigraphic density at fault zones (e.g., different lithologies on both sides of the fault), gravity anomaly gradient zones are formed, which can help identify fault distribution (e.g., the F1 and F2 basement faults appear as obvious gradient zones on the gravity anomaly map), providing a macroscopic tectonic background for calculating parameters such as fault distribution density and distance from basement faults.

[0073] The advantage of gravity data lies in its wide coverage and large detection depth (it can detect the basement), making it particularly suitable for the preliminary delineation of the structural framework in areas with low exploration levels. However, its resolution is relatively low, making it difficult to accurately invert the fine features of the target layer (such as the precise value of the target layer's burial depth). It needs to be used in conjunction with other high-resolution data.

[0074] Electrical resistivity data (such as magnetotelluric (MT) and controlled-source audio-frequency magnetotelluric (CSAMT)) primarily reflect the distribution differences of rock layers with different resistivities underground. Resistivity profiles can identify fault zones (low resistivity anomalies, often due to water infill or low-resistivity sediments), high-resistivity basement blocks (such as dense granite), and the distribution range of the target shale layer, providing crucial evidence for fault identification and stratigraphic lithology assessment. For example, basement fault zones, due to long-term activity leading to rock fracturing and water infill, typically have a resistivity <50Ω. m, manifested as a distinct low-resistivity anomaly zone (e.g., the F2 Shidongkou fault in the embodiment of this application shows a continuous low-resistivity anomaly on the MT section); the target shale, due to its high organic matter content and dense rock, typically has a higher resistivity than the overlying and underlying strata (e.g., the resistivity of the Niutitang Formation shale is 100-300Ω). m, higher than the 50-150Ω of the overlying Palang Formation mudstone. (m) can be used to delineate the target layer range through resistivity anomalies, which can assist in the inversion of the target layer burial depth.

[0075] The advantage of electrical resistivity data lies in its high sensitivity to fractures and lithological differences, and it can provide the vertical and lateral distribution characteristics of underground resistivity. It is especially suitable for identifying deep fractures and lithological boundaries of the target layer. However, it is greatly affected by topography and requires strict topographic correction. Furthermore, its lateral resolution is limited by the density of survey lines and needs to be combined with seismic data to improve accuracy.

[0076] Seismic data (especially 2D and 3D seismic data) can be used to precisely invert the layered structure of underground strata, the depth of the target layer, the attitude of the strata, and the precise location of faults through the reflection signals of seismic waves at the interfaces of rock strata with different acoustic impedances. This data is the core data for evaluating the parameters of the target layer. For example, by using the reflection axis characteristics of seismic profiles, the top and bottom interfaces of the target layer (such as the Niutitang Formation) can be accurately identified, and the depth of the target layer can be calculated (as in the embodiment of this application, the depth distribution of the Niutitang Formation was inverted using 2300 seismic depth points). By using the continuity and dip angle changes of the reflection axis, the attitude of the strata can be determined (e.g., a gentle reflection axis corresponds to a small dip angle of the strata, and a displaced reflection axis corresponds to a fault). By using the chaotic areas or displaced reflection axes of seismic reflections, the location and extension length of faults can be accurately identified (e.g., all 14 Cambrian bottom interface faults were identified through seismic profiles), providing a direct basis for the accurate calculation of parameters such as fault distribution density and strata attitude.

[0077] The advantages of seismic data are its high resolution (up to tens of meters) and ability to provide detailed stratigraphic information, making it the core data for evaluating the parameters of the target layer. However, it has high detection costs, relatively limited coverage (especially 3D seismic data), and is greatly affected by the quality of data processing (such as static correction and noise reduction). It needs to be combined with gravity and electrical resistivity data to improve the structural framework.

[0078] Single geophysical data has limitations. For example, gravity data alone cannot accurately invert the depth of the target layer, seismic data alone is insufficient to determine the boundaries of the regional tectonic framework, and electrical resistivity tomography (ERT) data alone cannot comprehensively identify the distribution of tectonic units. Therefore, selecting at least two data combinations (such as gravity + seismic, ERT + seismic, gravity + ERT + seismic) can achieve complementary advantages: for example, gravity data provides the regional tectonic framework, while seismic data provides the fine features of the target layer. Combining the two can improve the accuracy of the depth inversion of the target layer (e.g., in the embodiments of this application, the macroscopic range of the Jidong anticline is determined by gravity data, and then the precise depth of the Niutitang Formation within the anticline is inverted by seismic data); the fault low resistivity anomaly identified by ERT data and the fault reflection fault movement identified by seismic data mutually verify each other, which can improve the accuracy of fault identification (e.g., the F2 fault is confirmed by both the MT low resistivity anomaly and seismic reflection fault movement, avoiding misjudgment by single data).

[0079] In this embodiment, a combination of three data sources—gravity, electrical resistivity, and seismic—is used. Gravity data is used to delineate tectonic units, electrical resistivity data is used to identify fault and basement features, and seismic data is used to invert the depth of the target layer and the attitude of the strata. The three sources work together to provide comprehensive and reliable data support for the calculation of all evaluation parameters, ensuring the accuracy of the single-factor evaluation results.

[0080] Raw geophysical data typically includes non-geological factors such as topographic influence and noise interference. Direct use of these data can lead to deviations in structural analysis and parameter inversion results. Therefore, preprocessing is essential to ensure data quality meets evaluation requirements. The core objective of seismic data preprocessing is to improve the signal-to-noise ratio and resolution of reflection signals, ensuring clear identification of the reflection axis of the target layer. This mainly includes static correction, denoising, stacking, and migration processing. The core objective of gravity data preprocessing is to eliminate the influence of non-geological factors (such as topography, latitude, and intermediate layers) on gravity values ​​and extract residual gravity anomalies reflecting shallow subsurface structures. This mainly includes topographic correction, Bouguer correction, and separation of regional and local fields. The core objective of electrical resistivity data preprocessing is to eliminate noise interference and measurement errors to obtain reliable resistivity profiles. This mainly includes data editing, static correction, and inversion processing.

[0081] In summary, selecting at least two combinations of gravity, electrical resistivity, and seismic data, and performing rigorous preprocessing, can achieve complementary advantages and quality improvement of multi-source geophysical data. This provides high-quality data support for structural analysis (such as tectonic unit division and fault identification) and parameter inversion (such as target layer depth and stratigraphic attitude) of the evaluation area, ensuring the accuracy and reliability of single-factor evaluation results and avoiding evaluation bias caused by single data type or insufficient quality.

[0082] In some embodiments, it is applied to areas with low exploration levels, especially to marine shale gas exploration in areas with well-developed ancient uplift edges or faults.

[0083] Low-exploration-level areas are strategically important for shale gas exploration. However, due to limited exploration investment and a lack of basic data, traditional evaluation methods relying on formation pressure data are difficult to apply. The embodiments in this application, through a design that integrates multi-source geological and geophysical data without relying on formation pressure, precisely address the exploration challenges in this area. Tectonically complex areas (such as plate tectonics zones and the periphery of ancient uplifts) typically experience multiple phases of tectonic activity, resulting in densely developed faults, complex stratigraphic attitudes (e.g., large dip variations and severe erosion), and extremely uneven formation pressure distribution. Traditional methods rely on formation pressure data (such as well logging and well testing pressures), which are not only difficult to obtain but also lack representativeness (e.g., single-well pressure cannot reflect regional pressure distribution), making them unsuitable for evaluating preservation conditions at the regional scale. This method constructs a multi-factor index system incorporating tectonic modification parameters (fault density, distance from basement faults, and stratigraphic attitude) to directly quantify the degree of damage to preservation conditions caused by tectonic activity. For example, in areas with dense faults, the degree of damage can be quantified by fault density classification (e.g., >0.7 km / km). 2 Class IV) can quickly identify high-risk areas with severe formation fracturing; in steeply dipping formations, formation attitude classification (e.g., >20° is Class IV) can accurately determine unfavorable areas with strong lateral gas diffusion, and the evaluation can be completed without relying on formation pressure data.

[0084] For example, in the Majiang Uplift area of ​​this application embodiment (which has a complex structure and has experienced multiple tectonic activities during the Caledonian and Yanshanian periods), traditional methods cannot conduct a systematic evaluation of preservation conditions due to the lack of continuous stratigraphic pressure data; however, this method integrates seismic, gravity, and electrical resistivity data to evaluate parameters such as fault distribution and stratigraphic attitude, successfully delineating favorable areas and verifying its applicability in structurally complex areas.

[0085] In sparsely drilled areas (such as new blocks in the early stages of exploration), due to the small number of drilled wells (usually only 1-2 exploratory wells or no wells at all), it is difficult to obtain sufficient formation pressure data (e.g., single-well pressure data cannot reflect regional pressure changes), and the coverage of drilling data is limited, making it unsuitable for regional-scale evaluation. The core advantage of this method lies in relying on geological survey and geophysical exploration data (such as gravity, electrical, and seismic data) for evaluation. These data have the characteristics of wide coverage (e.g., 2D seismic survey lines can cover thousands of square kilometers) and high detection efficiency, enabling regional-scale parameter inversion and evaluation without relying on a large amount of drilling data. For example, the depth of the target layer can be inverted through seismic data (e.g., in this embodiment, 2300 seismic depth points cover 1200 km). 2 The evaluation area uses gravity and electrical resistivity data to identify fracture distribution, enabling comprehensive multi-factor evaluation even in sparsely drilled areas.

[0086] Taking a sparsely drilled ancient uplift edge area as an example, deploying only one exploration well is insufficient to obtain regional formation pressure data. However, by adopting this method, two-dimensional seismic survey lines (covering 500km) can be used to obtain this data. 2 The depth of the target layer was inverted, and structural units were identified by combining gravity data and fractures by electrical resistivity data. The preservation conditions were successfully evaluated, and two Class I favorable areas were delineated, providing clear target areas for subsequent drilling deployment and demonstrating its applicability in sparse drilling areas.

[0087] Obtaining formation pressure data relies on drilling logging (such as sonic logging and density logging to estimate pressure) or well testing (such as DST testing), which is costly and time-consuming. In areas with low exploration levels, formation pressure data is generally lacking due to limited drilling or no well testing operations, rendering traditional methods unusable. This method, from its initial design, abandons reliance on formation pressure data. It constructs an independent evaluation system by systematically screening parameters that are independent of pressure, such as the self-sealing capacity of the target layer, regional caprock conditions, and tectonic alteration. For example, the depth of the target layer reflects the formation pressure sealing capacity (the greater the depth, the higher the pressure sealing potential), the thickness of the direct caprock reflects the vertical sealing capacity, and tectonic alteration parameters reflect pressure destructive factors. The quality of preservation conditions can be indirectly evaluated without actual pressure data.

[0088] For example, in this embodiment of the application, only one exploration well in the evaluation area was logged, and no well test pressure data was obtained, so traditional methods could not be used for evaluation. However, this method obtained an accurate preservation condition score through the comprehensive evaluation of five non-pressure parameters. The evaluation results were compared with those of neighboring areas where pressure data had been obtained (e.g., the pressure coefficient of the adjacent Class I favorable area is >1.2, and the predicted pressure conditions of the Class I favorable area in this application are superior), which verified the effectiveness of the evaluation in areas lacking formation pressure data.

[0089] This application's embodiments are particularly applicable to marine shale gas exploration in areas with well-developed ancient uplift edges or faults. These areas are important target regions for marine shale gas exploration (e.g., Cambrian and Permian marine shale formations in southern China are mostly developed around ancient uplifts). However, the unique geological background of these areas leads to complex preservation conditions, which traditional methods struggle to address. The technical characteristics of this method are highly compatible with the exploration needs of these areas. Due to the uplift of ancient uplifts, the target strata in these areas exhibit significant differences in burial depth (e.g., shallow burial depth in the core and deep burial depth in the flanks) and uneven erosion (e.g., erosion easily occurs at the uplift edges, forming outcrops). Furthermore, influenced by the rigid blocks of the ancient uplifts, tectonic activity is dominated by thrust faults and folds, resulting in preservation conditions that are "locally favorable but overall complex." This method, through multi-factor evaluation, can accurately capture the differences in preservation conditions in these areas. To address the issue of large differences in burial depth, favorable areas with moderate burial depth (such as the wing of an ancient uplift) can be identified by classifying the burial depth of the target layer (e.g., Class I ≥ 2000m, Class IV ≤ 1000m). To address the issue of stratigraphic erosion, the severe shallow erosion areas can be avoided by classifying the distance from the surface outcrop of the target stratum (e.g., Class I ≥ 3.0 km). Based on the characteristics of tectonic activity, the gently sloping stratigraphic zones on the limbs of ancient uplifts can be identified by stratigraphic attitude classification (e.g., Class I 0°-10°), and the deep and large fault zones on the edges of ancient uplifts can be avoided by classification based on distance from basement faults (e.g., Class I ≥1.5km).

[0090] For example, in the embodiment of this application, located on the southwestern edge of the Xuefeng Uplift (the edge of the ancient uplift), the method successfully identified the central part of the Jidong Anticline (a gentle area on the wing of the ancient uplift, buried at a depth of 1500-2000m, and more than 3.0km from the outcrop) as a Class I favorable area. This is completely consistent with the favorable preservation pattern of "anticline core + moderate burial depth + far from faults" on the edge of the ancient uplift in this area, verifying its applicability in the edge region of the ancient uplift.

[0091] Fault-developed areas are high-risk zones for marine shale gas preservation, but "sweet spots" with localized, undeveloped faults (such as blocks between faults and the footwall of thrust faults) still possess exploration potential. Traditional methods, relying on formation pressure data, struggle to accurately identify these favorable local areas. This method, by using fault-related parameters (fracture distribution density, distance from basement faults) as core evaluation indicators, enables a refined assessment of preservation conditions in fault-developed areas. The fault distribution density parameter can quantify the degree of stratigraphic fragmentation in a region and identify "sweet spots" with sparse faults (such as those with a density ≤0.3 km / km). 2 Class I area); The distance parameter from the basement fracture can accurately avoid the influence range of deep and large fractures (such as Class IV areas ≤0.5km) and focus on stable blocks between fractures; By combining stratigraphic attitude parameters, we can further identify gently strata areas around the fault zone (such as gently strata on the footwall of a thrust fault with a dip angle of <10°). These areas are less affected by the fault and have high overlying pressure, resulting in excellent preservation conditions.

[0092] For example, in the region between faults F1 and F2 (fracture development zone) in this application embodiment, the method revealed a significant difference in fault distribution density within this region, with the fault density in the central part of the Jidong anticline ranging from 0.1 to 0.25 km / km. 2 (Class I) consists of stable blocks between faults, with a comprehensive score of 0.82-0.98, and is identified as a Class I favorable area; while the fault density in the area near the F2 fault is 0.7-1.2 km / km. 2 (Class IV), with a comprehensive score of <0.6, is a non-favorable area. It accurately identifies local favorable areas within the fault development zone, demonstrating the unique advantages of this type of region.

[0093] In summary, the embodiments of this application, through their design that does not rely on formation pressure, integrates multi-source geological and geophysical data, and focuses on tectonic alteration, are perfectly suited to low-exploration areas with complex structures, sparse drilling, and a lack of formation pressure data. Especially in marine shale gas exploration at the edges of ancient uplifts or where faults are developed, it can effectively solve the technical bottlenecks of traditional methods, providing a scientific and reliable technical means for strategic shale gas site selection in such areas, and has significant practical application value and prospects for promotion.

[0094] In summary, the embodiments of this application have the following beneficial effects: By systematically constructing a multi-factor evaluation index system covering the self-sealing property of the target layer (target layer burial depth), regional caprock conditions (direct caprock thickness), and tectonic alteration (fracture distribution density, distance from basement faults, distance from the target layer surface outcrop, stratigraphic attitude / structural style), this system comprehensively covers the "internal basis-external barrier-destructive factors" of shale gas preservation. This effectively solves the technical bottleneck of difficulty in evaluating preservation conditions in low-exploration areas with complex structures, sparse drilling, or lack of formation pressure data (especially marine shale gas exploration areas at the edge of ancient uplifts and with well-developed faults). Furthermore, through clear parameter grading standards (a I-IV level classification based on geological laws and empirical verification from neighboring areas) and scientific weight allocation (combining expert experience, comparison with neighboring areas, or statistical analysis, highlighting basement faults), this system effectively addresses the challenges of shale gas preservation. By incorporating key factors such as stratigraphic occurrence and quantitative weighted superposition calculations (fixed-level assignment and weighted summation method), the evaluation process is made objective, standardized, and repeatable, avoiding the subjective biases of traditional qualitative or semi-quantitative evaluations. Furthermore, this method fully integrates geological survey data with multi-source geophysical data such as gravity, electrical resistivity, and seismic data, accurately capturing differences in preservation conditions across different regions. It effectively identifies shale gas structural preservation areas with stable structures, strong capping capabilities, and low gas escape risk, providing scientific and reliable technical support for strategic shale gas area selection, target area optimization, and drilling deployment in low-exploration-level areas. This significantly improves the targeting and success rate of marine shale gas exploration, possessing significant theoretical value and broad application prospects in the field of unconventional natural gas exploration technology.

[0095] Based on the same inventive concept, this application also provides an apparatus for selecting favorable shale gas structural preservation areas without relying on formation pressure, corresponding to the method in the first embodiment that selects favorable shale gas structural preservation areas without relying on formation pressure. Since the principle of the apparatus in this application is similar to the above-mentioned method for selecting favorable shale gas structural preservation areas without relying on formation pressure, the implementation of the apparatus can refer to the implementation of the method, and the repeated parts will not be described again.

[0096] like Figure 2 As shown, Figure 2This is a schematic diagram of the apparatus 200 for selecting favorable shale gas structural preservation zones without relying on formation pressure, as provided in this application embodiment. The apparatus 200 for selecting favorable shale gas structural preservation zones without relying on formation pressure includes: Module 201 is used to select target study areas with shale gas exploration potential and determine the core exploration target stratigraphic units; Module 202 is used to screen parameters that do not depend on formation pressure data and can reflect the core influencing factors of the preservation conditions of the target layer based on the shale gas preservation mechanism of the target layer, and to construct a comprehensive evaluation index system that includes at least the self-sealing parameters of the target layer, the regional caprock condition parameters, and the tectonic modification parameters, so that the index system matches the geological background of the evaluation area and the characteristics of the target layer. The partitioning module 203 is used to conduct spatial distribution analysis on each parameter in the constructed multi-factor evaluation index system, and to pre-set a grading standard based on the geological laws of the evaluation area and the exploration experience of neighboring areas to divide each parameter into multiple levels, providing a standardized parameter level basis for subsequent quantitative calculations. The allocation module 204 is used to allocate weighting coefficients according to the degree of influence of each parameter on shale gas preservation conditions; The calculation module 205 is used to assign fixed scores to each of the divided levels, and multiply the scores of each parameter level obtained in each evaluation unit by the corresponding determined weight coefficients and then sum them up to obtain the comprehensive score of the construction and preservation conditions of the unit. The determination module 206 is used to delineate favorable areas for shale gas structure preservation based on the comprehensive scoring results.

[0097] Those skilled in the art should understand that Figure 2 The functions of each unit in the apparatus 200 shown for selecting favorable shale gas structural preservation areas without formation pressure can be understood with reference to the aforementioned description of the method for selecting favorable shale gas structural preservation areas without formation pressure. Figure 2 The functions of each unit in the apparatus 200, which does not select favorable shale gas structural preservation areas based on formation pressure, can be implemented by a program running on a processor or by specific logic circuits.

[0098] In one possible implementation, the target layer self-sealing parameter includes the target layer burial depth, the regional cap layer condition parameter includes the direct cap layer thickness, and the tectonic modification parameter includes at least three of the following: fault distribution density, distance from basement faults, distance from the surface outcrop of the target layer, and stratigraphic attitude / structural style.

[0099] In one possible implementation, the spatial distribution of each evaluation parameter is analyzed and classified into four levels: I, II, III, and IV, corresponding to preservation conditions from best to worst. The classification criteria are determined through geological pattern analysis and verification with neighboring areas.

[0100] In one possible implementation, the weighting coefficients are determined through expert experience, neighboring cell comparison, or statistical analysis, and the sum of the weighting coefficients of all parameters is 1.0.

[0101] In one possible implementation, the grade values ​​are assigned as follows: Grade I = 1.0, Grade II = 0.75, Grade III = 0.5, and Grade IV = 0.25. The comprehensive score is calculated using a weighted summation method.

[0102] In one possible implementation, geophysical exploration data includes at least two combinations of gravity, electrical, and seismic data, which are preprocessed for structural analysis and parameter inversion.

[0103] In one possible implementation, it is applied to areas with low exploration levels, especially to marine shale gas exploration in areas with well-developed ancient uplift edges or faults.

[0104] The aforementioned device, which does not prioritize shale gas conservation based on formation pressure, constructs a multi-factor evaluation index system encompassing the self-sealing properties of the target layer (target layer burial depth), regional caprock conditions (direct caprock thickness), and tectonic alteration (fracture distribution density, distance from basement faults, distance from the target layer surface outcrop, and stratigraphic attitude / structural style). This system comprehensively covers the "internal foundation, external barriers, and destructive factors" of shale gas conservation, effectively addressing the technical bottleneck of difficult conservation condition evaluation in low-exploration areas with complex structures, sparse drilling, or lack of formation pressure data (especially marine shale gas exploration areas at the edges of ancient uplifts and with well-developed faults). Furthermore, it utilizes clear parameter grading standards (a I-IV level classification based on geological laws and neighboring area experience) and scientific weight allocation (combining expert experience and comparison with neighboring areas). By employing statistical analysis (highlighting the influence of key factors such as basement faults and stratigraphic attitude) and quantitative weighted superposition calculations (fixed-level assignment and weighted summation method), the evaluation process achieves objectivity, standardization, and repeatability, avoiding the subjective biases of traditional qualitative or semi-quantitative evaluations. Furthermore, this method fully integrates geological survey data with multi-source geophysical data such as gravity, electrical resistivity, and seismic data, accurately capturing differences in preservation conditions across different regions. It effectively identifies shale gas structural preservation areas with stable structures, strong capping capacity, and low risk of gas escape, providing scientific and reliable technical support for strategic shale gas area selection, target area optimization, and drilling deployment in low-exploration-level areas. This significantly improves the targeting and success rate of marine shale gas exploration, possessing significant theoretical value and broad application prospects in the field of unconventional natural gas exploration technology.

[0105] like Figure 3 As shown, Figure 3 This is a schematic diagram of the composition structure of the electronic device 300 provided in the embodiments of this application. The electronic device 300 includes: The device 300 includes a processor 301, a storage medium 302, and a bus 303. The storage medium 302 stores machine-readable instructions executable by the processor 301. When the electronic device 300 is running, the processor 301 communicates with the storage medium 302 via the bus 303. The processor 301 executes the machine-readable instructions to perform the steps of the method for selecting favorable shale gas structure preservation areas without relying on formation pressure, as described in the embodiments of this application.

[0106] In practical applications, the various components in the electronic device 300 are coupled together via bus 303. It is understood that bus 303 is used to achieve communication between these components. In addition to a data bus, bus 303 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 3 The general designated all buses as Bus 303.

[0107] The aforementioned electronic equipment, through the systematic construction of a multi-factor evaluation index system covering the self-sealing property of the target layer (target layer burial depth), regional caprock conditions (direct caprock thickness), and tectonic alteration (fracture distribution density, distance from basement faults, distance from the target layer surface outcrop, stratigraphic attitude / structural style), comprehensively covers the "internal basis - external barriers - destructive factors" of shale gas preservation. This effectively solves the technical bottleneck of difficulty in conducting preservation condition evaluation in low-exploration areas with complex structures, sparse drilling, or lack of formation pressure data (especially marine shale gas exploration areas at the edge of ancient uplifts and with well-developed faults). Simultaneously, through clear parameter grading standards (a I-IV level division based on geological laws and neighboring area experience verification) and scientific weight allocation (combining expert experience, neighboring area comparisons, or statistical analysis, highlighting the fundamental factors), it effectively addresses the challenges of shale gas preservation. By incorporating key factors such as basal faults and stratigraphic attitude, and employing quantitative weighted superposition calculations (fixed-level assignment and weighted summation method), the evaluation process achieves objectivity, standardization, and repeatability, avoiding the subjective biases of traditional qualitative or semi-quantitative evaluations. Furthermore, this method fully integrates geological survey data with multi-source geophysical data such as gravity, electrical resistivity, and seismic data, accurately capturing differences in preservation conditions across different regions. It effectively identifies shale gas structural preservation areas with stable structures, strong capping capabilities, and low gas escape risk, providing scientific and reliable technical support for strategic shale gas area selection, target area optimization, and drilling deployment in low-exploration-level areas. This significantly improves the targeting and success rate of marine shale gas exploration, possessing significant theoretical value and broad application prospects in the field of unconventional natural gas exploration technology.

[0108] This application also provides a computer-readable storage medium storing executable instructions that, when executed by at least one processor 301, implement the method described in this application for selecting favorable shale gas structural preservation areas without relying on formation pressure.

[0109] In some embodiments, the storage medium may be a magnetic random access memory (FRAM), a read-only memory (ROM), or a programmable read-only memory (PROM). Erasable Programmable Read-Only Memory (EPROM) Electrically Erasable Programmable Read-Only Memory (EEPROM) Read-only memory, flash memory, magnetic surface storage, optical disc, or CD-ROM ROM, Compact Disc Read It can be a memory such as a memory only; or it can be a device that includes one or any combination of the above-mentioned memories.

[0110] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0111] As an example, executable instructions may, but do not necessarily, correspond to files in the file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0112] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0113] The aforementioned computer-readable storage medium, through the systematic construction of a multi-factor evaluation index system covering the self-sealing property of the target layer (target layer burial depth), regional caprock conditions (direct caprock thickness), and tectonic alteration (fracture distribution density, distance from basement faults, distance from the target layer surface outcrop, stratigraphic attitude / structural style), comprehensively covers the "internal basis-external barrier-destructive factors" of shale gas preservation. This effectively solves the technical bottleneck of difficulty in conducting preservation condition evaluation in low-exploration areas with complex structures, sparse drilling, or lack of formation pressure data (especially marine shale gas exploration areas with well-developed faults and ancient uplift margins). Simultaneously, through clear parameter grading standards (a I-IV level division based on geological laws and neighboring area experience verification) and scientific weight allocation (combining expert experience, neighboring area comparisons, or statistical analysis), it effectively addresses the challenges of shale gas preservation. This method emphasizes the influence of key factors such as basement faults and stratigraphic attitude, and employs quantitative weighted superposition calculations (fixed-level assignment and weighted summation method) to achieve objectivity, standardization, and repeatability in the evaluation process, avoiding the subjective biases of traditional qualitative or semi-quantitative evaluations. Furthermore, by fully integrating geological survey data with multi-source geophysical data such as gravity, electrical resistivity, and seismic data, it can accurately capture the differences in preservation conditions across different regions, effectively identifying shale gas structural preservation areas with stable structures, strong capping capacity, and low risk of gas escape. This provides scientific and reliable technical support for strategic shale gas area selection, target area optimization, and drilling deployment in low-exploration-level areas, significantly improving the targeting and success rate of marine shale gas exploration. It has significant theoretical value and broad application prospects in the field of unconventional natural gas exploration technology.

[0114] In the several embodiments provided in this application, it should be understood that the disclosed methods and electronic devices can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0115] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0116] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0117] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a platform server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0118] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for identifying a play fairway, preferably for shale gas, not based on formation pressure, characterized in that, The method comprises: selecting a target study area with shale gas exploration potential, and determining a core exploration target layer system; based on the shale gas preservation mechanism of the target layer system, screening parameters that do not depend on stratigraphic pressure data and can reflect the core influencing factors of the preservation conditions of the target layer, and constructing a comprehensive evaluation index system comprising at least the self-sealing parameter of the target layer, the regional caprock condition parameter and the tectonic reconstruction parameter, so that the index system is matched with the geological background and the characteristics of the target layer of the evaluation area; for each parameter in the multi-factor evaluation index system constructed, spatial distribution analysis is carried out, and each parameter is divided into multiple grades according to the preset grading standards of the geological laws of the evaluation area and the exploration experience of the adjacent area, which provides a standardized parameter grade basis for subsequent quantitative calculation; according to the influence degree of each parameter on the shale gas preservation condition, a weight coefficient is allocated; fixed scores are given to each grade, and the grade scores of each parameter obtained in each evaluation unit are multiplied by the corresponding weight coefficient determined and then added up to obtain the comprehensive score of the tectonic preservation condition of the unit. Based on the comprehensive score result, a favorable area of shale gas tectonic preservation is circled.

2. The method of claim 1, wherein, The self-sealing parameter of the target layer comprises the burial depth of the target layer, the regional caprock condition parameter comprises the thickness of the direct caprock, and the tectonic reconstruction parameter comprises at least three of the fracture distribution density, the distance from the basement fracture, the distance from the surface outcrop of the target layer and the stratigraphic occurrence / tectonic style.

3. The method of claim 2, wherein, The spatial distribution analysis and grading of each evaluation parameter adopt a four-grade grading method of I, II, III and IV, and the grading standards of the burial depth of the target layer are as follows: ≥2000m is type I, 1500-2000m is type II, 1000-1500m is type III, and ≤1000m is type IV; The grading standards of the thickness of the direct caprock are as follows: ≥250m is type I, 200-250m is type II, 150-200m is type III, and ≤150m is type IV; The grading standard of the fracture distribution density is: ≤0.3 km / km 2 Class I, 0.3-0.5 km / km 2 Class II, 0.5-0.7 km / km 2 Class III, >0.7 km / km 2 Class IV; The grading standards of the distance from the basement fracture are as follows: ≥1.5km is type I, 1.0-1.5km is type II, 0.5-1.0km is type III, and ≤0.5km is type IV; The grading standards of the distance from the surface outcrop of the target layer are as follows: ≥3.0km is type I, 2.0-3.0km is type II, 1.0-2.0km is type III, and ≤1.0km is type IV; The grading standards of the stratigraphic occurrence / tectonic style are as follows: 0°-10° is type I, 10°-15° is type II, 15°-20° is type III, and >20° is type IV.

4. The method of claim 2, wherein, The allocation of the weight coefficient is as follows: the distance from the basement fracture is 0.3, the stratigraphic occurrence is 0.25, the fracture distribution density is 0.2, the burial depth of the target layer is 0.15, and the distance from the surface outcrop of the target layer is 0.

1.

5. The method of claim 1, wherein, The grade value is I level=1.0, II level=0.75, III level=0.5, and IV level=0.25, and the comprehensive score is calculated by weighted summation method.

6. The method of claim 1, wherein, The geophysical exploration data comprises at least two combinations of gravity, electrical method and seismic data, which are used for tectonic analysis and parameter inversion after pretreatment.

7. The method according to any one of claims 1 to 6, characterized in that, It is applied to marine shale gas exploration in low exploration degree areas, especially in paleo-uplift edge or fracture developed areas.

8. An apparatus for identifying a play fairway without relying on formation pressure, preferably for shale gas, characterized in that, The device comprises: The selecting module is configured to select a target research area with shale gas exploration potential and determine a core exploration target layer series; The constructing module is configured to screen parameters that are independent of formation pressure data and can reflect core influencing factors of preservation conditions of the target layer series based on shale gas preservation mechanisms of the target layer series, and construct a comprehensive evaluation index system including at least self-sealing parameters of the target layer, regional caprock condition parameters and tectonic reconstruction parameters, so that the index system is matched with the geological background of the evaluation area and the characteristics of the target layer; The dividing module is configured to analyze spatial distribution of each parameter in the constructed multi-factor evaluation index system, and divide each parameter into multiple grades according to preset grading standards of geological laws of the evaluation area and exploration experience of adjacent areas, so as to provide standardized parameter grade basis for subsequent quantitative calculation; The distributing module is configured to distribute weight coefficients according to the influence degree of each parameter on the shale gas preservation conditions; The calculating module is configured to assign fixed scores to each grade, and multiply and accumulate the grade scores of each parameter obtained in each evaluation unit with the corresponding weight coefficients to obtain a comprehensive score of the tectonic preservation conditions of the unit. The determining module is configured to delineate a shale gas tectonic preservation favorable area based on the comprehensive score result.

9. An electronic device, comprising: The processor, the storage medium and the bus, the storage medium stores the machine readable instructions executable by the processor, when the electronic equipment runs, the processor and the storage medium communicate through the bus, the processor executes the machine readable instructions, to execute the method for not selecting the shale gas tectonic preservation favorable area based on formation pressure as claimed in any one of claims 1 to 7. The computer readable storage medium stores the computer program, and the computer program is executed by the processor to execute the method for not selecting the shale gas tectonic preservation favorable area based on formation pressure as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, ​

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