High clay shale oil in-situ reservoir accumulation dynamics mechanism and mode evaluation method

Abstract

The application relates to the technical field of unconventional oil and gas exploration, in particular to a high-clay shale oil in-situ accumulation dynamics mechanism and mode evaluation method, which comprises the following steps: collecting fluid pressure, temperature data, displacement pressure, oiliness, brittleness index, hydrostatic pressure, vitrinite reflectance and density values of shale samples at each depth position point of a probe well of each survey point; calculating abnormal sensitivity; then obtaining ground temperature evaluation credibility; obtaining self-adaptive fitting weight; obtaining actual fluid pressure of the probe well of each survey point at each depth; obtaining pressure coefficients of shale samples at each depth position point of the probe well of each survey point; obtaining self-sealing accumulation mode and retention accumulation mode of shale oil; and constructing a shale oil enrichment area evaluation comprehensive index based on vitrinite reflectance, oiliness, brittleness index and pressure coefficient to evaluate high-clay shale in-situ flow. The application improves the accuracy of evaluation of high-clay shale in-situ self-sealing accumulation, retention accumulation and dynamics mechanism.

Description

Technical Field

[0001] This application relates to the field of unconventional oil and gas exploration technology, specifically to the in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil. Background Technology

[0002] After more than 60 years of development, Daqing Oilfield's conventional oil and gas resources have entered the later stages of exploration, while unconventional oil and gas resources such as Gulong Shale oil have become an important continuation for the oilfield's high-quality development. The Gulong Shale has an average clay content exceeding 35%, giving its reservoirs extremely strong plasticity. Simultaneously, the complex inherent foliation fractures in the Gulong Shale make horizontal fractures advantageous channels for fracturing fluid flow. However, the combined effect of clay minerals and complex foliation fracture morphology makes it difficult for horizontal fractures to extend, resulting in relatively high extraction difficulty.

[0003] Current research on hydrocarbon accumulation dynamics mainly focuses on conventional and tight hydrocarbons, employing similar methodologies that emphasize reservoir microstructure analysis (pore-throat structure), the coupling relationship between charging dynamics and pore-throat resistance, and the characterization of the drainage system. However, for the Gulong shale reservoir, characterized by its integrated source and reservoir structure and large-scale continuous accumulation of primary source and reservoir, research on the self-enclosed enrichment dynamics mechanism and model of high-clay continental shale oil is lacking. This hinders the understanding of the formation mechanism, controlling factors, and theoretical advancements in large-scale shale oil enrichment zones, as well as large-scale exploration for increased reserves and efficient production. Therefore, this application proposes an evaluation method for the in-situ accumulation dynamics mechanism and model of high-clay shale oil. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a dynamic mechanism and model evaluation method for in-situ accumulation of high-clay shale oil, thereby resolving existing issues.

[0005] The technical solution adopted in this application for the in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil is as follows:

[0006] One embodiment of this application provides a dynamic mechanism and model evaluation method for in-situ accumulation of high-clay shale oil, the method comprising the following steps:

[0007] The fluid pressure, temperature, displacement pressure, oil content, brittleness index, hydrostatic pressure, vitrinite reflectance, and density values ​​of shale samples were collected from various depths of the exploration wells at each survey point.

[0008] The predicted curves of exploration wells at each exploration point are obtained by using a curve fitting algorithm combined with a mineral database.

[0009] The anomaly sensitivity of exploration wells at each depth point is obtained based on the predicted curves and fluid pressure.

[0010] Based on the correlation between the temperature data and fluid pressure of each shale sample and the temperature data and fluid pressure of other shale samples, the reliability of geothermal assessment at each depth point of the exploration well at each exploration point is obtained.

[0011] The curve fitting algorithm was used to process the depth and fluid pressure of all depth measurement points of the exploration wells at each exploration point to obtain the measurement curves of the exploration wells at each exploration point.

[0012] Based on the differences between the radii of curvature of each exploration point on the measured curve and the predicted curve, the reliability of geothermal assessment and the sensitivity to anomalies, the adaptive fitting weights of each exploration point at each depth location of the well are obtained.

[0013] Based on depth, fluid pressure, adaptive fitting weights, and the predicted curves of the wells at each exploration point, the fitting curves of the wells at each exploration point are obtained. Based on the fitting curves, the actual fluid pressure of the wells at each exploration point at each depth is obtained. Based on the actual fluid pressure and hydrostatic pressure, the pressure coefficients of shale samples at each depth location of the wells at each exploration point are obtained.

[0014] The in-situ accumulation mode of high-clay shale oil is evaluated based on the relationship between the displacement pressure and the actual fluid pressure, and the self-enclosed accumulation mode and the stagnant accumulation mode of shale oil are obtained.

[0015] A comprehensive evaluation index for shale oil enrichment areas was constructed based on vitrinite reflectance, oil content, brittleness index, and pressure coefficient to evaluate the in-situ accumulation dynamics of high-clay shale oil.

[0016] Furthermore, the method for obtaining the prediction curve is as follows:

[0017] For the density values ​​of shale samples at various depths of the exploration wells at each exploration point, the fluid pressure corresponding to the density value of each shale sample is obtained from the mineral database of the region where each exploration point is located as the standard fluid pressure of the shale sample density value. A curve fitting algorithm is used to fit the depth of each depth of the exploration wells at each depth point to the standard fluid pressure of the shale sample at the depth, and the predicted curve of the exploration wells at each exploration point is obtained.

[0018] Furthermore, the method for obtaining the abnormal sensitivity is as follows:

[0019] The difference in tangent slope at each depth point of the exploration well is obtained based on the slope of the tangent line on the predicted curve at each depth point.

[0020] The formula for calculating the abnormal sensitivity is: α h =k h ×Δd; where α h This represents the abnormal sensitivity of fluid pressure at the h-th depth location of each exploration point; k h-1and k h+1 denoted as the slopes of the tangents on the prediction curve at the (h-1)th depth point and the (h+1)th depth point of each exploration point, respectively, and Δd represents the absolute value of the difference between the fluid pressure at the h-th depth point of each exploration point and the standard fluid pressure of the shale sample at the h-th depth point.

[0021] Furthermore, the method for obtaining the difference in tangent slope is as follows:

[0022] For each depth point of the exploration well at each exploration point, calculate the absolute value of the difference between the slope of the tangent line on the predicted curve of the exploration well for the previous adjacent depth point and the slope of the tangent line on the predicted curve of the exploration well for the next adjacent depth point. This value is used as the difference value of the tangent slope for each depth point of the exploration well at each exploration point.

[0023] Furthermore, the method for obtaining the reliability of the ground temperature assessment is as follows:

[0024] Based on temperature data and fluid pressure, feature vectors of shale samples at various depths of exploration wells at each survey point were obtained.

[0025] Obtain the neighborhood of each depth location point of the exploration well at each survey point;

[0026] The formula for calculating the reliability of the geothermal assessment is as follows: In the formula, β h The reliability of geothermal assessment for shale samples at the h-th depth location of each exploration point is given by N, where N is the number of depth locations within the neighborhood of the h-th depth location of each exploration point, cos() is the cosine similarity, and T is the geothermal similarity. i T represents the feature vector of the shale sample at the i-th depth location within the neighborhood of the h-th depth location of each exploration point. h This represents the feature vector of the shale sample at the h-th depth location of each exploration point.

[0027] Furthermore, the method for obtaining the feature vector is as follows:

[0028] For shale samples at various depths of the exploration wells at each exploration point, the vector composed of temperature data and fluid pressure of the shale samples is used as the feature vector of the shale samples at each depth.

[0029] Furthermore, the method for obtaining the neighborhood is as follows:

[0030] For each exploration point, the area between the nearest predetermined number of depth points is taken as the neighborhood of each depth point.

[0031] Furthermore, the method for obtaining the adaptive fitting weights is as follows:

[0032] Based on the differences in the radius of curvature between the measured and predicted curves at each exploration point, the reliability of geothermal assessment, and the sensitivity to anomalies, adaptive fitting coefficients for each depth location of the exploration well at each exploration point are obtained. The normalized values ​​of the adaptive coefficients are used as the adaptive fitting weights for each depth location of the exploration well at each exploration point.

[0033] Furthermore, the formula for calculating the adaptive fitting coefficient is as follows: In the formula, ω h β represents the adaptive fitting weight of the h-th depth location point of each exploration point; h α represents the reliability of geothermal assessment of shale samples at the h-th depth of each exploration well. h Δρ represents the abnormal sensitivity of fluid pressure at the h-th depth location of each exploration point. h δ represents the absolute value of the difference between the radius of curvature of the measured curve and the predicted curve of the exploration well at each exploration point at the h-th depth; δ is the preset parameter adjustment factor.

[0034] Furthermore, the method for obtaining the fitted curve is as follows:

[0035] For each exploration point, the depth, fluid pressure, adaptive fitting weight, and predicted curve of the exploration point are used as inputs to the B-spline curve fitting algorithm to obtain the fitting curve of the exploration point.

[0036] Furthermore, the method for obtaining the actual fluid pressure is as follows: the fluid pressure at each depth of the exploration well at each exploration point on the fitted curve is obtained as the actual fluid pressure at each depth location.

[0037] Furthermore, the method for obtaining the pressure coefficient is as follows:

[0038] For shale samples at various depths of the exploration wells at each exploration point, the ratio of actual fluid pressure to hydrostatic pressure is calculated as the pressure coefficient of the shale samples at various depths of the exploration wells at each exploration point.

[0039] Furthermore, the method for obtaining the retention and accumulation mode is as follows:

[0040] For each exploration point, calculate the average actual fluid pressure and the average displacement pressure of the exploration well at all depth locations. When the average actual fluid pressure is greater than or equal to the average displacement pressure, the exploration well at the exploration point is in the stagnant reservoir formation mode.

[0041] Furthermore, the method for obtaining the self-enclosed accumulation mode is as follows:

[0042] When the average value of the actual fluid pressure is less than the average value of the displacement pressure, the exploration well at the survey point is in a self-enclosed reservoir formation mode.

[0043] Furthermore, the characteristics of shale oil in the aforementioned stagnant accumulation mode are as follows:

[0044] The average daily production of vertical and inclined wells containing shale oil reservoirs is 3.59 t / d;

[0045] The oil from the retained sedimentary reservoirs is a medium-quality oil with a density greater than 0.82 g / cm³. 3 The average density is 0.843 g / cm³. 3 The average viscosity is 16.24 mm. 2 / s; the average wax content is 26.48%; the average freezing point is 22.1℃; the average molecular weight is 391.8 g / mol; the saturated hydrocarbon content of the shale oil that has accumulated in reservoirs is greater than 70%, the average saturated hydrocarbon content is 79.8%, and the average aromatic hydrocarbon content is 13.5%.

[0046] Furthermore, the self-enclosed shale oil reservoir is characterized by:

[0047] The average daily production of vertical wells in self-sealed shale reservoirs is 3.84 t / d, and the average daily production of horizontal wells is 21.49 t / d. The gas-oil ratio is greater than 100 m³ / d. 3 / m 3 ;

[0048] Self-sealed shale oil reservoirs are classified as volatile to light oils with a density of less than 0.82 g / cm³. 3 The average density is 0.80 g / cm³. 3 Viscosity less than 10 mm 2 / s, average viscosity is 4.35mm 2 / s; wax content less than 25%, average wax content 20.11%; freezing point less than 20℃, average freezing point 13.7℃; molecular weight less than 350 g / mol, average molecular weight 310.6 g / mol; saturated hydrocarbon content greater than 80%, average saturated hydrocarbon content 90%; aromatic hydrocarbon content less than 10%, average aromatic hydrocarbon content 4.5%.

[0049] Furthermore, the formation and evolution characteristics of the self-enclosed hydrocarbon accumulation mode and the stagnant hydrocarbon accumulation mode are as follows:

[0050] The formation and evolution characteristics of the self-enclosed hydrocarbon accumulation mode and the stagnant hydrocarbon accumulation mode can be divided into three stages: the reflectance of the vitrinite in the first stage is less than 0.9%; the reflectance of the vitrinite in the second stage is greater than or equal to 0.9% and less than 1.6%; and the reflectance of the vitrinite in the third stage is greater than or equal to 1.6%.

[0051] Furthermore, the process of transitioning between the self-enclosed accumulation mode and the stagnant accumulation mode is as follows:

[0052] The transformation process of storage state between the self-enclosed accumulation mode and the stagnant accumulation mode is divided into two stages. The first stage is the low-to-medium evolution stage, in which the vitrinite reflectance is less than or equal to 1.0%. The second stage is the high-to-medium evolution stage, in which the vitrinite reflectance is greater than 1.0%.

[0053] Furthermore, the construction of the comprehensive evaluation index for shale oil enrichment areas includes:

[0054] For shale samples at each depth of the exploration wells at each exploration point, calculate the product of vitrinite reflectance with its preset weighting coefficient, the product of oil content with its preset weighting coefficient, the product of brittleness index with its preset weighting coefficient, and the product of pressure coefficient with its preset weighting coefficient. The sum of all products is used as the comprehensive index for evaluating shale oil enrichment areas of shale samples at each depth of the exploration wells at each exploration point.

[0055] Furthermore, the evaluation of in-situ flow in high-clay shale includes:

[0056] The comprehensive index for evaluating shale oil enrichment areas of shale samples at various depths of all exploration wells is normalized. If the normalized value of the shale oil enrichment area is greater than the preset threshold, the exploration point is considered a favorable enrichment area for Gulong shale oil; otherwise, the exploration point is not considered a favorable enrichment area for Gulong shale oil.

[0057] This application has at least the following beneficial effects:

[0058] This embodiment primarily utilizes a comprehensive geological experimental analysis method encompassing core sampling, hydrocarbon generation, reservoir formation, and hydrocarbon accumulation in shale oil exploration drilling. Through studies of hydrocarbon generation, expulsion, and retention characteristics, pore structure evolution, and the coupling relationship between expulsion pressure and formation fluid pressure, it reveals the accumulation model and dynamic mechanism of the Gulong shale oil. Furthermore, based on a combination of well testing measurements and exploration inference methods, and considering the differences between measured and inferred values, as well as the variations in temperature distribution and fluid pressure at different well depths, different fitting weights for measured fluid pressures are obtained, leading to a fitting relationship between well depth and fluid pressure. Simultaneously, the relationship between expulsion pressure and maturity is derived using capillary pressure curves, with maturity serving as the medium for the coupling relationship between fluid pressure and expulsion pressure. Therefore, this embodiment proposes for the first time that the Gulong shale oil exhibits two accumulation models: a shale oil retention accumulation model where fluid pressure is greater than or equal to the expulsion pressure, and a shale oil self-sealing accumulation model where fluid pressure is less than the expulsion pressure. Based on different hydrocarbon accumulation models, this approach effectively guides the selection, zoning, and classification of "sweet spots" in the Gulong continental shale oil fields of the Songliao Basin, leading to breakthroughs in these areas. It also extends the lower limit of exploration depth to 2600m and increases the sweet spot area from 5800km². 2 Expanded to 13,000 km2 The proven reserves are 204 million tons, and the production is 465,000 tons of oil equivalent. Attached Figure Description

[0059] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 A flowchart illustrating the in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil provided in this application;

[0061] Figure 2 This is a graph showing the relationship between the production of regenerated and retained hydrocarbons and the vitrinite reflectance, provided in one embodiment of this application.

[0062] Figure 3 A three-stage characteristic diagram of the evolution of Gulong shale oil is provided as an embodiment of this application;

[0063] Figure 4 A diagram illustrating the diagenetic evolution stages provided in one embodiment of this application;

[0064] Figure 5 A graph showing the relationship between maximum orifice throat radius and discharge pressure provided in one embodiment of this application;

[0065] Figure 6 A schematic diagram of the fitting curve provided for one embodiment of this application;

[0066] Figure 7 A porosity and frequency distribution diagram provided for one embodiment of this application;

[0067] Figure 8 A graph showing the relationship between rejection pressure and maturity level is provided for one embodiment of this application;

[0068] Figure 9 A diagram showing the relationship between retained and self-sealed shale oil reservoirs and their properties, provided as an embodiment of this application;

[0069] Figure 10 This is a diagram showing the relationship between Ro and the gas-oil ratio in one embodiment of this application;

[0070] Figure 11 This is a distribution map of favorable enrichment areas for shale oil reservoirs that are trapped and self-enclosed, provided as an embodiment of this application. Detailed Implementation

[0071] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation methods, structures, features, and effects of the in-situ accumulation dynamics mechanism and model evaluation method for high-clay shale oil proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0072] 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 pertains.

[0073] The following section, in conjunction with the accompanying drawings, details the specific scheme of the in-situ accumulation dynamics mechanism and model evaluation method for high-clay shale oil provided in this application.

[0074] This application provides an embodiment of the in-situ accumulation dynamics mechanism and model evaluation method for high-clay shale oil. Specifically, it provides the following in-situ accumulation dynamics mechanism and model evaluation method for high-clay shale oil. Please refer to [link / reference]. Figure 1 The method includes the following steps:

[0075] Step S1: Collect fluid pressure, temperature data, displacement pressure, oil content, brittleness index, hydrostatic pressure, vitrinite reflectance, and density values ​​of shale samples at various depths of the exploration wells at each survey point.

[0076] The Songliao Basin, located in northeastern China, covers an area of ​​26 × 10⁴ square kilometers. It has a two-layered structure with a lower fault and an upper depression. The upper depression layer developed during the Late Cretaceous and is a large terrestrial freshwater-slightly brackish water depression lacustrine basin sedimentary deposit. From bottom to top, it contains the Quantou Formation, Qingshankou Formation, Yaojia Formation, Nenjiang Formation, Sifangtai Formation, and Mingshui Formation. The Qingshankou and Nenjiang Formations are semi-deep lacustrine to deep lacustrine facies high-clay, organic-rich shale formed by two large-scale intrusions during the Late Cretaceous. The lithology is mainly lamellar and layered shale, interbedded with small amounts of thin-layered siltstone, shell limestone, and dolomite. The Qingshankou Formation shale has high organic matter abundance, with an average TOC of 2.2% and a maximum of 13.2%. It also exhibits high maturity, with Ro generally exceeding 0.75% in the central depression area, reaching a maximum of 1.67%. Furthermore, it generates a large amount of oil, accounting for 89% of the total oil generation in the entire depression, making it the primary source rock in the Songliao Basin depression. Around this primary source rock, the Qingshankou Formation, the Songliao Basin depression has formed a complete hydrocarbon system consisting of conventional oil and gas from the upper source (Sartu, Putaohua, and Gaotaizi), source (Gulong shale oil), and source (Fuyang-Yangdachengzi tight oil).

[0077] Studies on the contribution ratio of oil sources show that more than half of the oil and gas in Daqing Changyuan comes from the source rocks of the Qingshankou Formation in the Qijia-Gulong Depression; nearly half of the oil generation is retained in the Qingshankou Formation shale, forming Gulong shale oil.

[0078] During the formation of shale oil, as the burial depth increases and the temperature rises, the organic matter in the shale begins to undergo thermal evolution. This is helpful for analyzing the current state of the Gulong shale oil in the region and for shale oil extraction. The following analysis focuses on exploratory wells at a single exploration point.

[0079] A hot-pressing simulation experiment using a capsule reactor (implemented according to standard ZL201910207260.9) was conducted to simulate the generation, expulsion, and retention of hydrocarbons in shale. A plunger sample and a "sandwich" loading method (shale in the middle, quartz sand on top and bottom) were used. Vitrin reflectance of shale samples at various depths of exploration wells at each survey point was obtained using a microphotometer with an oil immersion objective. This approach aimed to more closely approximate the formation conditions for hydrocarbon generation, expulsion, and retention, thus obtaining a graph showing the relationship between the production of generation, expulsion, and retention hydrocarbons and vitrinite reflectance (Ro). (See figure below.) Figure 2 As shown.

[0080] Analysis of the relationship between the production of source, expulsion, and retained hydrocarbons and the vitrinite reflectance (Ro) reveals that the Ro values ​​for source, expulsion, and retained oil in the Gulong Shale are mainly between 0.9% and 1.6%, with the main peak Ro values ​​around 1.1% to 1.3%. For source oil exceeding 2%, the main peak is 6.12%; for retained oil exceeding 1.8%, the main peak is 4.9%; and for expulsion oil exceeding 0.4%, the main peak is 1.29%. This indicates that compared to the classic Tissot oil generation model, the Gulong Shale exhibits a wider maturity range for its source, expulsion, and retained oil windows, still possessing oil generation potential even at Ro levels reaching 1.9%, with the oil generation amounting to 22% of the peak value.

[0081] Shale oil exists primarily in two states: free and adsorbed. Based on the conservation of matter in hydrocarbon generation, most free oil is formed by the cracking and transformation of adsorbed oil, while a small amount is produced as hydrocarbon generation products from kerogen cracking. The occurrence state and evolution model of shale oil were obtained through rock pyrolysis analysis and chloroform bitumen "A" data. It should be noted that rock pyrolysis data were obtained using the national standard "Rock Pyrolysis Analysis" (GB / T18602-2012), and chloroform bitumen "A" data were obtained using the industry standard "Determination of Chloroform Bitumen in Rocks" (SY / T5118-2005).

[0082] Based on the vitrinite reflectance Ro, the evolution of Gulong shale oil is divided into three stages, and the evolution of Gulong shale oil exhibits three-stage characteristics. Figure 3(1) In the first stage, the reflectance Ro of the vitrinite group is <0.9%, mainly kerogen oil generation, with free oil accounting for 20% to 40% of the retained oil, mainly adsorbed oil; (2) In the second stage, the reflectance Ro of the vitrinite group is 0.9% to 1.6%, and a large amount of adsorbed oil is converted into free oil, with free oil accounting for 40% to 80% of the retained oil. At the same time, due to the transformation of the occurrence state, the volume of shale oil expands and begins to form overpressure; (3) In the third stage, the reflectance Ro of the vitrinite group is >1.60%, and shale oil begins to crack into gas, but the amount of free oil is much higher than that of the conventional oil generation mode. Due to the large amount of shale oil being converted into natural gas, the formation overpressure reaches its maximum, with a pressure coefficient of about 1.6.

[0083] Furthermore, quantitative results from kerogen and mineral matrix and pore fissures showed that, with the vitrinite reflectance Ro1.0% as the boundary, the occurrence state of Gulong shale oil underwent two transformations: in the low-to-medium evolution stage, shale oil transformed from being mainly found in kerogen to being mainly found in rock and organic pore fissures (organic clay composite pores); in the high-to-medium evolution stage, shale oil transformed from an adsorbed state to a free state.

[0084] Different shale diagenetic evolution stages determine the maturity of organic matter in shale, thus affecting shale oil formation. Therefore, shale diagenetic analysis helps determine the timing and potential of hydrocarbon generation. Pore structure directly determines the size and capacity of shale oil reservoirs. Therefore, studying pore structure helps to understand the reservoir capacity and seepage patterns of shale oil in reservoirs. In addition, the evolution of displacement pressure reflects the changes in the dynamics experienced by shale oil during its formation. The magnitude and evolution of displacement pressure are important indicators for assessing the dynamics of shale oil formation and the conditions of initial migration.

[0085] The current burial depth of the Gulong shale oil is mainly between 1000m and 2600m, with measured vitrinite reflectance (Ro) ranging from 0.5% to 1.6%, and maximum pyrolysis temperatures (Tmax) mostly between 435℃ and 460℃. Based on the diagenetic stage classification criteria for clastic rocks, and considering various indicators such as clay mineral evolution and diagenesis, the shale diagenetic evolution stage in this area is mainly in the late early diagenetic stage to the middle diagenetic stage B, specifically as follows... Figure 4 As shown, diagenesis manifests differently at different evolutionary stages, resulting in varying reservoir characteristics; the two influence each other and evolve synergistically.

[0086] In the early diagenetic stage, shale is shallowly buried, with relatively loose matrix particle contact, low-maturity organic matter, and pore types mainly consisting of intergranular and intercrystalline pores. In the intermediate diagenetic stage A, with increasing burial depth and temperature, mechanical compaction intensifies, matrix particles become more tightly packed, intergranular pore sizes decrease, and compaction promotes the drainage of interlayer water from clay minerals, leading to the transformation of illite-montmorillonite mixed layers into illite, and a decrease in lattice spacing. During this stage, organic matter matures, and hydrocarbon generation releases organic matter pores. Simultaneously, acidic fluids such as organic acids and carbon dioxide dissolve easily soluble minerals like feldspar and carbonates in the reservoir, creating some micron-sized dissolution pores, thus increasing porosity. In the intermediate diagenetic stage B, with further burial depth and increased geothermal temperature, organic matter becomes over-mature, and solid bituminous material cracks to form gaseous hydrocarbons, generating numerous nanoscale organic matter crack pores, which become the main reservoir space for shale.

[0087] The Gulong Shale is mainly composed of mud-sized felsic grains, clay minerals, carbonate minerals, and organic matter, forming a reservoir space system primarily composed of nanoscale pores, including intergranular pores, intercrystalline pores of clay minerals, and pores in organic matter. To investigate the unique nanopore structure of the shale and clarify the evolution of pore throat size and formation displacement pressure, high-pressure mercury intrusion porosimetry (HIP) experiments were conducted. The analysis results confirmed that the shale pore throats are extremely small, with pore throat radii mostly less than 40 nm, and that the pore structure characteristics are closely related to the shale maturity.

[0088] During the early diagenetic stage, organic matter is in a low-maturity stage. At this time, the pore throat radius of shale is less than 100 nm, mainly concentrated in the range of less than 40 nm. The reservoir pore structure is relatively homogeneous and has good connectivity. The formation displacement pressure is usually distributed between 10 and 30 MPa. Figure 5 (Point A).

[0089] During the intermediate diagenetic stage A, organic matter was in a mature and peak hydrocarbon generation phase. At this stage, the shale pore structure was still dominated by throat radii smaller than 40 nm, accounting for about 80%–90% of the volume. However, due to the effects of hydrocarbon generation and organic acid dissolution, some micron-sized pores and throats appeared in the shale, with the maximum throat radius reaching 500–600 nm. The homogeneity of the reservoir pore structure deteriorated, and the maximum displacement pressure of the formation did not exceed 30 MPa. The displacement pressure of reservoirs with well-developed dissolution pores was less than 15 MPa. With increased thermal evolution, during the intermediate diagenetic stage B, organic matter was in a highly mature stage. Shale reservoir space was dominated by nanoscale organic pores, with even smaller throat radii, mainly concentrated in the <10 nm range. At this time, the displacement pressure of shale reservoirs was mostly higher than 50 MPa. Figure 5 (Point B) This is mainly because the finer pore throat structure increases the resistance to fluid flow, requiring higher pressure to expel the fluid, thus causing shale oil to be trapped in the shale reservoir at this stage.

[0090] Shale reservoir fluid pressure is a crucial driving force for shale oil migration within the reservoir. After shale oil formation, uneven fluid pressure distribution within the reservoir creates pressure differentials, which drive shale oil migration from high-pressure areas to low-pressure areas. Therefore, analyzing shale reservoir fluid pressure can measure shale oil migration. Displacement pressure, on the other hand, is the critical pressure at which shale oil begins to exit the shale pores and migrate, determining the time and conditions under which shale oil begins to move within the shale. Therefore, optimizing the magnitude and distribution of displacement pressure affects the migration path of shale oil.

[0091] To address the enrichment and accumulation mechanism of high-clay continental shale oil, core samples were drilled at depths ranging from 1000m to 2600m for each exploration well. Shale samples were collected at every 20m depth. Fluid pressure and temperature data at each depth were obtained using pressure gauges and thermocouples. In addition, density wells were used to obtain the density values ​​of the shale samples at each depth. The density well method is a well-known technique and will not be described in detail in this embodiment.

[0092] The oil content of shale samples at various depths of wells at various exploration points was obtained using solvent extraction, and the brittleness index of shale samples at various depths of wells at various exploration points was obtained using X-ray diffraction whole-rock analysis. Solvent extraction and X-ray diffraction whole-rock analysis are well-known techniques and will not be described in detail in this embodiment.

[0093] The capillary pressure curve method was used to obtain the displacement pressure of shale samples at various depths of the exploration wells at each survey point. The capillary pressure curve method is a well-known technique and will not be described in detail in this embodiment.

[0094] The hydrostatic pressure of shale samples at each depth of the exploration well at each exploration point is calculated. The method for calculating the hydrostatic pressure is a well-known technique and will not be described in detail in this embodiment.

[0095] Step S2: Use a curve fitting algorithm combined with a mineral database to obtain the predicted curves of the exploration wells at each exploration point; based on the predicted curves and fluid pressure, obtain the anomaly sensitivity of the exploration wells at each depth location.

[0096] Fluid pressure, also known as formation pressure, refers to the pressure of fluids within the pores of a formation. Currently, the main methods for studying reservoir fluid pressure are the well test method and the well data inference method. While the well test method offers higher accuracy, the pressure data is limited. The well data inference method, on the other hand, infers pressure data based on the material composition of shale samples at each depth, making it susceptible to the influence of the complex downhole environment, leading to inaccuracies in the inferred fluid pressure. Both methods have their advantages and disadvantages. To obtain more accurate shale reservoir fluid pressure data, this application combines and complements the well test method and the well data inference method to obtain a relationship between well depth and fluid pressure that approximates the actual downhole conditions. The specific implementation process is as follows:

[0097] In this embodiment, the inference method based on in-depth data is density wells. The basic principle is that when the formation fluid pressure changes, the density of shale changes. When the fluid pressure increases, the rock pores are compressed, and the rock density increases.

[0098] Specifically, for the density values ​​of shale samples at various depths from the exploration wells at each exploration point, the fluid pressure corresponding to the density value of each shale sample is obtained from the mineral database of the region where each exploration point is located, and used as the standard fluid pressure of the shale sample density value. The least squares method is used to perform curve fitting between the depth of each exploration well at each depth and the standard fluid pressure of the shale sample at that depth, to obtain the prediction curve of the exploration well at each exploration point. The mineral database and the least squares method are well-known technologies and will not be described in detail in this embodiment.

[0099] Furthermore, the oil testing method involves directly placing sensors at the corresponding depth points to obtain actual fluid pressure data, which more closely approximates downhole fluid pressure data. However, due to the characteristics of actual high-clay shale, there are numerous shale fractures in the well, resulting in heterogeneity. This means that the rock properties of the shale reservoir vary significantly at different locations, leading to uneven fluid distribution. Measurements at a single location only reflect the pressure at that specific depth and do not reflect the overall relationship between well depth and fluid pressure. Additionally, these measurements are susceptible to temperature gradient changes, potentially underestimating or overestimating fluid pressure. Therefore, a comprehensive analysis combining actual measurements and inferred values ​​is necessary.

[0100] Under ideal conditions for the same well, the fluid pressure data obtained through oil testing and the fluid pressure values ​​inferred by density probing should be consistent. The greater the difference between the two data points at a certain depth, the higher the degree of anomaly in the data at that depth, and the greater the influence of shale heterogeneity. Furthermore, fluid pressure increases with depth, and the relationship between the two is non-linear. However, because the depth points are relatively close together, the change in measured fluid pressure at adjacent depth points is approximately linear. If the change in measured fluid pressure at adjacent depth points deviates significantly, it further indicates a greater influence of shale heterogeneity at that location.

[0101] Based on the above analysis, the anomaly sensitivity of each depth point of the exploration well at each survey point is obtained based on the predicted curve and fluid pressure. The method for obtaining this sensitivity is as follows:

[0102] For each depth point of the exploration well at each exploration point, calculate the absolute value of the difference between the slope of the tangent line on the predicted curve of the exploration well for the previous adjacent depth point and the slope of the tangent line on the predicted curve of the exploration well for the next adjacent depth point. This value is used as the difference value of the tangent slope for each depth point of the exploration well at each exploration point.

[0103] Furthermore, the anomaly sensitivity at each depth point of the exploration well at each survey point is calculated using the following formula: α h =k h ×Δd; where α h This represents the abnormal sensitivity of fluid pressure at the h-th depth location of each exploration point; k h-1 and k h+1 denoted as the slopes of the tangents on the prediction curve at the (h-1)th depth point and the (h+1)th depth point of each exploration point, respectively, and Δd represents the absolute value of the difference between the fluid pressure at the h-th depth point of each exploration point and the standard fluid pressure of the shale sample at the h-th depth point.

[0104] It should be noted that the anomaly sensitivity is set to zero for the initial and final depth positions.

[0105] It should be noted that the greater the influence of shale changes at the current depth location, the greater the difference between the measured fluid pressure value and the standard fluid pressure value at the corresponding location on the prediction curve, resulting in a larger value of Δd. At the same time, the weaker the correlation between fluid pressures at adjacent locations at this location, the greater the difference in slope, and ultimately the greater the value of the anomaly sensitivity at this depth location.

[0106] Step S3: Based on the correlation between the temperature data and fluid pressure of each shale sample and the temperature data and fluid pressure of other shale samples, obtain the geothermal assessment reliability of each depth point of the exploration well at each exploration point.

[0107] Meanwhile, in sedimentary basins, geothermal temperature increases with depth, and the two are approximately linearly correlated. As geothermal temperature increases, fluid expands, resulting in increased fluid pressure.

[0108] Based on the above analysis, for shale samples at various depths of the exploration wells at each exploration point, the vector composed of temperature data and fluid pressure of the shale samples is used as the feature vector of the shale samples at each depth. The feature vector can reflect the influence of shale properties on the shale samples at each depth, such as natural fractures and fracture development. Therefore, if the feature vector of a single depth point differs significantly from that of its neighbors, it indicates that the depth point is located at a natural fracture or where shale properties are affected, suggesting that the reliability of the depth point is low.

[0109] Furthermore, for each depth location of the exploration well at each exploration point, the area between the Nth depth location point and the nearest depth location point is taken as the neighborhood of each depth location point. In this embodiment, N is 6, but the implementer can select other values ​​according to the actual situation.

[0110] Based on the above analysis, the reliability of geothermal assessment of shale samples at various depths from exploration wells at each survey point is obtained based on the correlation between feature vectors. The calculation formula is as follows: In the formula, β h The reliability of geothermal assessment for shale samples at the h-th depth location of each exploration point is given by N, where N is the number of depth locations within the neighborhood of the h-th depth location of each exploration point, cos() is the cosine similarity, and T is the geothermal similarity. i T represents the feature vector of the shale sample at the i-th depth location within the neighborhood of the h-th depth location of each exploration point. h This represents the feature vector of the shale sample at the h-th depth location of each exploration point.

[0111] It should be noted that, ideally, the geothermal value increases linearly with depth. This linear increase in geothermal temperature leads to a greater expansion effect on the fluid, but the relationship between geothermal temperature and fluid pressure remains largely consistent. This results in similar feature vectors at different depths, leading to a higher reliability value for the geothermal assessment at that depth. Conversely, if the current depth is affected by shale properties, the difference between this depth and neighboring depths will be greater, resulting in a lower reliability value for the geothermal assessment.

[0112] Step S4: Use a curve fitting algorithm to process the depth and fluid pressure of all depth measurement points of the exploration well at each exploration point to obtain the measurement curve of the exploration well at each exploration point; based on the difference between the radius of curvature of each exploration point on the measurement curve and the predicted curve, the reliability of geothermal assessment and the sensitivity of anomalies, obtain the adaptive fitting weight of each depth location point of the exploration well at each exploration point.

[0113] Data measured at each depth point can more accurately reflect the fluid pressure at the current location. However, at some abnormal depth points, the deviation from the overall well depth and fluid pressure distribution may be large. In contrast, the inference method of density exploration wells may be directly related to the shale density at a single depth point and the shale condition over a larger area. Therefore, the inference method is more accurate in predicting the fluid pressure at the gap depth between adjacent depth points. Thus, it is necessary to combine the advantages of both methods to obtain a comprehensive relationship between well depth and fluid pressure.

[0114] For shale samples at all depth locations, if the distribution of the measured fluid pressure is close to the distribution on the predicted curve, it indicates that the measured data at that depth location and the inferred data of the blank depth are closer to the truth; conversely, it indicates that the inferred data at that depth location and the blank depth are far from the truth.

[0115] Furthermore, the least squares method was used to perform curve fitting on the depth and fluid pressure of all depth measurement points of the exploration well at each exploration point to obtain the measurement curve of the exploration well at each exploration point.

[0116] Based on the above analysis, and considering the differences in the radii of curvature between the measured and predicted curves for each exploration point, the reliability of geothermal assessment, and anomaly sensitivity, adaptive fitting weights for each depth location of the well at each exploration point are obtained. The method for obtaining these weights is as follows:

[0117] Calculate the adaptive fitting coefficients for each depth location of the exploration well at each survey point. The calculation formula is as follows: In the formula, ω h β represents the adaptive fitting weight of the h-th depth location point of each exploration point; h α represents the reliability of geothermal assessment of shale samples at the h-th depth of each exploration well. h Δρ represents the abnormal sensitivity of fluid pressure at the h-th depth location of each exploration point. h δ represents the absolute value of the difference between the radius of curvature of the measured curve and the predicted curve of the exploration well at each exploration point at the h-th depth; δ is the preset parameter adjustment factor.

[0118] Furthermore, the normalized value of the adaptive coefficient is used as the adaptive fitting weight for each depth location of the exploration well at each exploration point.

[0119] By considering the distribution trends between the measured and predicted curves' radii of curvature at a given depth, the closer their distributions are, the smaller the difference in radii of curvature, indicating that the data at that depth is closer to reality. Furthermore, the less the shale material affects the depth and the more uniform the temperature gradient distribution, the higher the reliability of the geothermal assessment and the lower the anomaly sensitivity. Ultimately, a higher adaptive weight for that depth indicates a greater attraction of that depth to the fitted curve when fitting depth and fluid pressure. Conversely, when the measured data is significantly affected and the assessment deviates greatly from reality, a lower adaptive fitting weight indicates a less attractive fit to the fitted curve when fitting depth and fluid pressure.

[0120] At this point, the adaptive fitting weights for the h-th depth location of the exploration well at each survey point are obtained.

[0121] Step S5: Based on depth, fluid pressure, adaptive fitting weights, and the predicted curves of the exploration wells at each exploration point, obtain the fitting curves of the exploration wells at each exploration point, and obtain the actual fluid pressure of the exploration wells at each depth based on the fitting curves.

[0122] Furthermore, for each exploration point's well, the depth, fluid pressure, adaptive fitting weights, and predicted curves of the wells at all depth locations are used as inputs to the B-spline curve fitting algorithm to obtain the fitted curves for each exploration point's well. The B-spline curve fitting algorithm is a well-known technique and will not be elaborated upon in this embodiment. A schematic diagram of the fitted curve is shown below. Figure 6 As shown. The fitted curve more accurately obtains the fluid pressure at the depth of the exploration well at each exploration point, and obtains the fluid pressure at each depth of the exploration well at each exploration point as the actual fluid pressure at each depth.

[0123] Step S6: Obtain the pressure coefficient of shale samples at each depth point of the exploration well at each survey point based on the actual fluid pressure and hydrostatic pressure.

[0124] Based on the above results, and based on the actual fluid pressure at each depth of the exploration wells at each exploration point, an analysis was conducted on all areas of the Gulong Shale. The results are shown in Table 1. Due to the different burial depths and thermal evolution histories experienced, the actual fluid pressure and pressure coefficient vary greatly in different areas.

[0125] For shale samples at various depths of the exploration wells at each exploration point, the ratio of actual fluid pressure to hydrostatic pressure is calculated as the pressure coefficient of the shale samples at various depths of the exploration wells at each exploration point.

[0126] Among them, the Qijia Gulong Depression has the largest burial depth, ranging from 1900 to 2600 m. The shale has generally experienced the peak of oil generation, and the actual fluid pressure of the shale reservoir is high, with the highest pressure coefficient reaching 1.8 and an average of 1.38. The Changyuan Depression has undergone a significant uplift after the deposition of the Qingshankou Formation, and its maturity and evolution are relatively low. The shale has generally just entered the hydrocarbon generation stage, and the actual fluid pressure of the shale reservoir is basically at normal pressure. The Sanzhao Depression has a maturity and evolution level between the two, and the actual fluid pressure of the shale reservoir is between normal pressure and abnormally high pressure.

[0127] Table 1. Statistics of Predicted Pressure and Pressure Coefficient of Gulong Shale Exploration Wells

[0128]

[0129]

[0130]

[0131] Displacement pressure is a key parameter characterizing reservoir properties. It reflects not only the rock pore structure but also its permeability and reservoir performance. Under specific hydrocarbon accumulation conditions, it is a controlling parameter that determines whether oil and gas can break through the reservoir interface and accumulate. This embodiment uses the capillary pressure curve method to study the pore throat size and displacement pressure characteristics of the Gulong Shale, specifically following the "Determination of Rock Capillary Pressure Curves" (GB / T29171-2023).

[0132] like Figure 7 As shown, the porosity of the Gulong shale is less than 10%, mainly distributed between 2% and 9%, accounting for 92% of the total, with an average of 5.1%. The permeability is relatively low, mainly between 0.001×10⁻³ μm² and 0.01×10⁻³ μm², accounting for 68% of the total, while the permeability between 0.01×10⁻³ μm² and 1×10⁻³ μm² accounts for 25%. This indicates that the Gulong shale has moderate porosity but low permeability. Further research is needed on the shale displacement pressure characteristics to analyze the shale oil accumulation process.

[0133] Simultaneously, based on the correlation analysis of exhaustion pressure and maturity evolution, such as Figure 8 As shown, when Ro is from 0.5% to 0.8%, the exhaust pressure varies little, with an average value between 9.65 and 13.78 MPa. When Ro is greater than 0.8%, the exhaust pressure increases rapidly. When Ro is from 0.8% to 1.3%, the average exhaust pressure increases from 16.53 to 43.21 MPa, showing a large range of variation. When Ro is greater than 1.3%, the exhaust pressure is greater than 20 MPa, with an average value generally greater than 40 MPa, reaching a maximum of 50.3 MPa.

[0134] Step S7: Evaluate the in-situ accumulation mode of high-clay shale oil based on the relationship between the displacement pressure and the actual fluid pressure, and obtain the self-enclosed accumulation mode and the stagnant accumulation mode of shale oil.

[0135] To investigate the hydrocarbon accumulation characteristics of the Gulong shale oil, this example studies the coupling relationship between actual fluid pressure and displacement pressure. After Ro exceeds 0.7%, the fluid pressure in the Gulong shale increases significantly due to the initiation of substantial hydrocarbon generation, exceeding the hydrostatic pressure and continuing to increase steadily. Before Ro reaches 1.2%, the displacement pressure remains close to the hydrostatic pressure and lower than the fluid pressure; however, after Ro exceeds 1.2%, the displacement pressure begins to increase rapidly and quickly surpasses the fluid pressure. Fluid pressure is the driving force of hydrocarbon accumulation, while displacement pressure is the resistance. Based on the fluid pressure envelope and displacement pressure trend line of the Gulong shale, the coupling relationship between the two was discovered, controlling the two types of hydrocarbon accumulation modes in the Gulong shale oil.

[0136] The first type is the reservoir formation model. When the Ro content is between 0.7% and 1.3%, the Gulong Shale generates a large amount of oil. The actual fluid pressure is greater than the displacement pressure. After the shale's adsorption capacity is met, the Gulong Shale begins to discharge a large amount of oil to form a conventional oil reservoir. This is the main force behind Daqing Oilfield's cumulative crude oil production exceeding 2.5 billion tons. The shale oil remaining in the Gulong Shale forms a reservoir.

[0137] The second type is the self-enclosed reservoir formation model. When Ro is greater than 1.3%, the Gulong Shale continuously generates hydrocarbons. At this point, the actual fluid pressure is less than the displacement pressure, and the Gulong Shale stops venting hydrocarbons, thus sealing in a large amount of oil and gas, forming a self-enclosed reservoir. This is achieved by calculating the average actual fluid pressure and the average displacement pressure at all depths for each exploration well. When the average actual fluid pressure is less than the average displacement pressure, the exploration well at that point is considered to be in a self-enclosed reservoir formation model. For example, the shale oil discovered in wells such as Gulong Oil Ping 1 belongs to this self-enclosed reservoir formation model. This type of shale oil is the mainstay of the Gulong Shale oil, with a resource volume of approximately 5.4 billion tons and proven geological reserves exceeding 200 million tons.

[0138] Gulong shale oil is a typical continental shale oil, with oil enriched in shale fractures and matrix pores. Clay mineral content is as high as 35% or more, located in the lower part of the Qingyi and Qinger sections of the Lower Cretaceous. The depositional period was generally a transgressive period, a semi-deep lacustrine to deep lacustrine subfacies depositional environment. The tectonics were stable during the depositional period, with stable subsidence of the paleolake basin. The lithology is dominated by mudstone and shale, accounting for over 85%, in addition to thin layers of fine sandstone, siltstone, ostracod limestone, dolomite, and tuff. Laminar thickness is mostly less than 0.01 m. Reservoir space is mainly matrix pores and fractures, with total porosity of 2%–15%, averaging 7.9%, and effective porosity of 2%–8%, averaging 3.7%. Gulong shale is a black shale rich in organic matter deposited during a global Late Cretaceous anoxic event. The source material is singular, lacustrine type I, dominated by stratiform algae, with high organic matter abundance, averaging 2.69%, and an average S1 concentration of 6.47 mg / g. The stagnant and self-enclosed reservoir formation models of the Gulong shale oilfield occurred at different stages of maturity evolution, and the differences in their reservoir characteristics are mainly related to the hydrocarbon characteristics generated by the shale at different maturity evolution stages. This application utilizes crude oil physical property data from 255 wells in the Gulong shale oilfield, along with oil testing results, to study the reservoir characteristics of stagnant and self-enclosed reservoir areas.

[0139] Retained shale oil reservoirs are mainly distributed in the Qijia Depression, Sanzhao Depression, and the surrounding areas of the Gulong Depression. Daily production from vertical or deviated wells ranges from 1.36 to 6.72 tons, with an average of 3.59 tons / day. Horizontal wells produce 10.2 to 13.2 tons / day. They do not produce water and have low gas yields. Retained shale oil reservoirs are classified as medium-quality oil. Figure 9 The density is generally greater than 0.82 g / cm3, with an average of 0.843 g / cm3; the average viscosity is 16.24 mm2 / s, with a main frequency between 10 and 20 mm2 / s; the wax content is relatively high, averaging 26.48%; the average freezing point is 22.1℃, with a main frequency between 15℃ and 30℃; the average molecular weight is 391.8 g / mol, with a main frequency between 370 and 410 g / mol (Table 2).

[0140] Compared to crude oil from conventional sandstone reservoirs in the Qingshankou Formation, the distribution range of physical properties is similar, but the average and dominant frequency ranges are lower. This is mainly due to differences in crude oil composition. The shale oil retained in the reservoir has a higher saturated hydrocarbon content, exceeding 70%, with an average of 79.8%; and an aromatic hydrocarbon content between 8% and 18%, with an average of 13.5%. In contrast, the crude oil from conventional sandstone reservoirs in the Qingshankou Formation has a dominant saturated hydrocarbon content between 55% and 75%, with an average of 65.31%; and an aromatic hydrocarbon content between 14% and 24%, with an average of 19.5%. This difference is because the earlier-formed crude oil discharged hydrocarbons and injected into the conventional reservoir, while the oil retained in the shale is a later-formed oil with a relatively higher maturity.

[0141] Table 2. Statistical Table of Physical Properties of Gulong Shale Oil

[0142]

[0143] * Minimum value - Maximum value

[0144] average value

[0145] Self-sealed shale oil reservoirs are mainly distributed within the Gulong Depression. The daily production of vertical wells is similar to that of stagnant shale oil wells, ranging from 1.95 to 5.472 t / d, with an average of 3.84 t / d. However, the daily production of horizontal wells is twice that of stagnant shale oil wells, ranging from 12.54 to 28.611 t / d, with an average of 21.49 t / d. Some wells produce water, accompanied by gas production, with a daily gas production of 180–11506 m³ and a gas-oil ratio greater than 100 m³. 3 / m 3 ( Figure 10 Self-sealed shale oil reservoirs are light in quality, belonging to volatile to light oils, with a density generally less than 0.82 g / cm³. 3 Average 0.80 g / cm³ 3 Viscosity less than 10 mm 2 / s, average, 4.35mm 2 / s; wax content is still relatively high, less than 25%, averaging 20.11%; pour point is less than 20℃, averaging 13.7℃; molecular weight is less than 350 g / mol, averaging 310.6 g / mol. Compared with stagnant shale oil, its physical properties are significantly lower. In terms of crude oil composition, saturated hydrocarbon content is high, greater than 80%, averaging 90%; aromatic hydrocarbon content is less than 10%, averaging 4.5%.

[0146] Step S8: Based on vitrinite reflectance, oil content, brittleness index, and pressure coefficient, a comprehensive evaluation index for shale oil enrichment areas is constructed to evaluate the in-situ accumulation dynamics of high-clay shale oil.

[0147] Based on the above studies on shale oil formation, evolution, diagenesis, and pressure, it was found that after the Ro content of the Gulong Shale exceeded 1.3%, the shale oil became lighter in quality, had a higher gas-oil ratio, and experienced a displacement pressure greater than the fluid pressure, thus forming a self-sealing shale oil reservoir. Statistics on the oil production from horizontal wells in the self-sealing reservoir zone (Ro>1.3%) showed a production rate greater than 20 t / d, while the production rate from shale oil in the stagnant reservoir zone was less than 5 t / d.

[0148] In addition to being influenced by the dynamic mechanism of shale oil accumulation, the production of Gulong shale oil is also controlled by geological sweet spots such as oil content and nuclear magnetic resonance macropores, as well as engineering sweet spots such as brittle minerals and pressure coefficients.

[0149] Based on the above analysis, a comprehensive evaluation index for shale oil enrichment areas is obtained by performing multivariate nonlinear analysis on shale oil production at various depths of exploratory wells at each exploration point using vitrinite reflectance Ro, oil content S1, brittleness index, and pressure coefficient. The method is as follows: for shale samples at various depths of exploratory wells at each exploration point, the products of vitrinite reflectance and its preset weighting coefficient, oil content and its preset weighting coefficient, brittleness index and its preset weighting coefficient, and pressure coefficient and its preset weighting coefficient are calculated respectively. The sum of all these products is taken as the comprehensive evaluation index for shale oil enrichment areas at various depths of shale samples at each exploration point. In this embodiment, the preset weighting coefficients for oil content S, pressure coefficient, vitrinite reflectance Ro, and brittleness index are 0.4, 0.3, 0.2, and 0.1, respectively. The implementer may select other values ​​based on actual conditions.

[0150] Furthermore, the comprehensive index for evaluating shale oil enrichment zones of shale samples at various depths of all exploration wells was normalized. If the normalized value of the shale oil enrichment zone is greater than a preset threshold, the exploration point is evaluated as a favorable enrichment zone for Gulong shale oil; otherwise, the exploration point is not considered a favorable enrichment zone for Gulong shale oil. Figure 11 As shown, the in-situ dynamic mechanism evaluation of high-clay shale is completed. In this embodiment, the preset threshold value is 0.8, but the implementer can select other values ​​according to the actual situation.

[0151] The above examples illustrate the entire process of the present invention for evaluating the self-sealing hydrocarbon accumulation dynamics mechanism and model of high-clay shale. The evaluation results of the self-sealing hydrocarbon accumulation dynamics mechanism and model of high-clay shale can be used for shale oil exploration and production.

[0152] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this application. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0153] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0154] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them; modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions of some of the technical features, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A dynamic mechanism and model evaluation method for in-situ accumulation of high-clay shale oil, characterized in that, The method includes the following steps: The fluid pressure, temperature, displacement pressure, oil content, brittleness index, hydrostatic pressure, vitrinite reflectance, and density values ​​of shale samples were collected from various depths of the exploration wells at each survey point. The predicted curves of exploration wells at each exploration point are obtained by using a curve fitting algorithm combined with a mineral database. The anomaly sensitivity of exploration wells at each depth point is obtained based on the predicted curves and fluid pressure. Based on the correlation between the temperature data and fluid pressure of each shale sample and the temperature data and fluid pressure of other shale samples, the reliability of geothermal assessment at each depth point of the exploration well at each exploration point is obtained. The curve fitting algorithm was used to process the depth and fluid pressure of all depth measurement points of the exploration wells at each exploration point to obtain the measurement curves of the exploration wells at each exploration point. Based on the differences between the radii of curvature of each exploration point on the measured curve and the predicted curve, the reliability of geothermal assessment and the sensitivity to anomalies, the adaptive fitting weights of each exploration point at each depth location of the well are obtained. Based on depth, fluid pressure, adaptive fitting weights, and the predicted curves of the wells at each exploration point, the fitting curves of the wells at each exploration point are obtained. Based on the fitting curves, the actual fluid pressure of the wells at each exploration point at each depth is obtained. Based on the actual fluid pressure and hydrostatic pressure, the pressure coefficients of shale samples at each depth location of the wells at each exploration point are obtained. The in-situ accumulation mode of high-clay shale oil is evaluated based on the relationship between the displacement pressure and the actual fluid pressure, and the self-enclosed accumulation mode and the stagnant accumulation mode of shale oil are obtained. A comprehensive evaluation index for shale oil enrichment areas was constructed based on vitrinite reflectance, oil content, brittleness index, and pressure coefficient to evaluate the in-situ accumulation dynamics of high-clay shale oil. The method for obtaining the prediction curve is as follows: For the density values ​​of shale samples at each depth point of the exploration well at each exploration point, the fluid pressure corresponding to the density value of each shale sample is obtained from the mineral database of the area where each exploration point is located as the standard fluid pressure of the shale sample density value. The curve fitting algorithm is used to perform curve fitting between the depth of each depth point of the exploration well at each exploration point and the standard fluid pressure of the shale sample at the depth, so as to obtain the prediction curve of the exploration well at each exploration point. The method for obtaining the abnormal sensitivity is as follows: The difference in tangent slope at each depth point of the exploration well is obtained based on the slope of the tangent line on the predicted curve at each depth point. The formula for calculating the anomaly sensitivity is: ; In the formula, This indicates the abnormal sensitivity of fluid pressure at the h-th depth location of each exploration point; and Let represent the slopes of the tangent lines on the prediction curve at the (h-1)th depth point and the (h+1)th depth point of each exploration well, respectively. This represents the absolute value of the difference between the fluid pressure at the h-th depth of the well at each exploration point and the standard fluid pressure of the shale sample at the h-th depth. The method for obtaining the difference in tangent slope is as follows: For each depth point of the exploration well at each exploration point, calculate the absolute value of the difference between the slope of the tangent line of the preceding adjacent depth point on the prediction curve of the exploration well and the slope of the tangent line of the following adjacent depth point on the prediction curve of the exploration well. This value is used as the difference value of the tangent slope of each depth point of the exploration well at each exploration point. The method for obtaining the reliability of the geothermal assessment is as follows: Based on temperature data and fluid pressure, feature vectors of shale samples at various depths of exploration wells at each survey point were obtained. Obtain the neighborhood of each depth location point of the exploration well at each survey point; The formula for calculating the reliability of the geothermal assessment is as follows: In the formula, To assess the reliability of geothermal evaluation of shale samples at the h-th depth location of each exploration well. N Let be the number of depth points in the neighborhood of the h-th depth point of each exploration point, and let cos() be the cosine similarity. This represents the feature vector of the shale sample at the i-th depth location within the neighborhood of the h-th depth location of each exploration point. The feature vector of the shale sample at the h-th depth of the well at each exploration point; The method for obtaining the feature vector is as follows: For shale samples at various depths of the exploration wells at each exploration point, the vector composed of temperature data and fluid pressure of the shale samples is used as the feature vector of the shale samples at each depth. The method for obtaining the neighborhood is as follows: For each depth location of the exploration well at each exploration point, the area between the nearest preset number of depth location points is taken as the neighborhood of each depth location point; The method for obtaining the adaptive fitting weights is as follows: Based on the differences between the radii of curvature of each exploration point on the measured curve and the predicted curve, the reliability of geothermal assessment and the sensitivity to anomalies, the adaptive fitting coefficients of each exploration point's well at each depth are obtained, and the normalized values ​​of the adaptive coefficients are used as the adaptive fitting weights of each exploration point's well at each depth. The formula for calculating the adaptive fitting coefficient is: In the formula, The adaptive fitting weight represents the h-th depth location point of each exploration point; This indicates the reliability of the geothermal assessment of shale samples at the h-th depth location of each exploration point. This represents the abnormal sensitivity of fluid pressure at the h-th depth location of each exploration point. This represents the absolute value of the difference between the radius of curvature of the measured curve and the predicted curve of the well at each exploration point at the h-th depth. This is a preset parameter tuning factor; The method for obtaining the fitted curve is as follows: For each exploration point, the depth, fluid pressure, adaptive fitting weight, and predicted curve of each exploration point are used as inputs to the B-spline curve fitting algorithm to obtain the fitting curve of each exploration point. The method for obtaining the actual fluid pressure is as follows: obtain the fluid pressure at each depth of the exploration well at each exploration point on the fitted curve as the actual fluid pressure at each depth location.

2. The in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil as described in claim 1, characterized in that, The method for obtaining the pressure coefficient is as follows: For shale samples at various depths of the exploration wells at each exploration point, the ratio of actual fluid pressure to hydrostatic pressure is calculated as the pressure coefficient of the shale samples at various depths of the exploration wells at each exploration point.

3. The in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil as described in claim 1, characterized in that, The method for obtaining the retention and accumulation mode is as follows: For each exploration point, calculate the average actual fluid pressure and the average displacement pressure of the exploration well at all depth locations. When the average actual fluid pressure is greater than or equal to the average displacement pressure, the exploration well at the exploration point is in the stagnant reservoir formation mode.

4. The in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil as described in claim 3, characterized in that, The method for obtaining the self-enclosed accumulation mode is as follows: When the average value of the actual fluid pressure is less than the average value of the displacement pressure, the exploration well at the survey point is in a self-enclosed reservoir formation mode.

5. The in-situ accumulation dynamics mechanism and model evaluation method for high-clay shale oil as described in claim 3, characterized in that, The characteristics of shale oil in the aforementioned retention and accumulation model are: The average daily production of vertical and inclined wells containing shale oil reservoirs is 3.59 t / d; The oil from the retained sedimentary reservoirs is a medium-quality oil with a density greater than 0.82 g / cm³. 3 The average density is 0.843 g / cm³. 3 The average viscosity is 16.24 mm. 2 / s; the average wax content is 26.48%; the average freezing point is 22.1℃; the average molecular weight is 391.8 g / mol; the saturated hydrocarbon content of the shale oil that has been deposited in the reservoir is greater than 70%, the average saturated hydrocarbon content is 79.8%, and the average aromatic hydrocarbon content is 13.5%.

6. The in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil as described in claim 4, characterized in that, The characteristics of shale oil in the self-enclosed accumulation mode are as follows: The average daily production of vertical wells in self-sealed shale reservoirs is 3.84 t / d, and the average daily production of horizontal wells is 21.49 t / d. The gas-oil ratio is greater than 100 m³ / d. 3 / m 3 ; Self-sealed shale oil reservoirs are classified as volatile to light oils with a density of less than 0.82 g / cm³. 3 The average density is 0.80 g / cm³. 3 Viscosity less than 10 mm 2 / s, average viscosity is 4.35mm 2 / s; wax content less than 25%, average wax content 20.11%; freezing point less than 20℃, average freezing point 13.7℃; molecular weight less than 350g / mol, average molecular weight 310.6g / mol; saturated hydrocarbon content greater than 80%, average saturated hydrocarbon content 90%; aromatic hydrocarbon content less than 10%, average aromatic hydrocarbon content 4.5%.

7. The in-situ accumulation dynamics mechanism and model evaluation method for high-clay shale oil as described in claim 1, characterized in that, The formation and evolution characteristics of the self-enclosed hydrocarbon accumulation mode and the stagnant hydrocarbon accumulation mode are as follows: The formation and evolution characteristics of the self-enclosed hydrocarbon accumulation mode and the stagnant hydrocarbon accumulation mode can be divided into three stages: the reflectance of the vitrinite in the first stage is less than 0.9%; the reflectance of the vitrinite in the second stage is greater than or equal to 0.9% and less than 1.6%; and the reflectance of the vitrinite in the third stage is greater than or equal to 1.6%.

8. The in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil as described in claim 1, characterized in that, The process of transformation between the self-enclosed accumulation mode and the stagnant accumulation mode is as follows: The transformation process of storage state between the self-enclosed accumulation mode and the stagnant accumulation mode is divided into two stages. The first stage is the low-to-medium evolution stage, in which the vitrinite reflectance is less than or equal to 1.0%; the second stage is the high-to-medium evolution stage, in which the vitrinite reflectance is greater than 1.0%.

9. The in-situ accumulation dynamics mechanism and model evaluation method of high-clay shale oil as described in claim 1, characterized in that, The comprehensive index for evaluating shale oil enrichment areas includes: For shale samples at various depths of wells at each exploration point, calculate the product of vitrinite reflectance with its preset weighting coefficient, the product of oil content with its preset weighting coefficient, the product of brittleness index with its preset weighting coefficient, and the product of pressure coefficient with its preset weighting coefficient. The sum of all products is used as the comprehensive index for evaluating shale oil enrichment areas of shale samples at various depths of wells at each exploration point.

10. The in-situ accumulation dynamics mechanism and model evaluation method for high-clay shale oil as described in claim 9, characterized in that, The evaluation of the in-situ accumulation dynamics of high-clay shale oil includes: The comprehensive index for evaluating shale oil enrichment areas of shale samples at various depths of all exploration wells is normalized. If the normalized value of the shale oil enrichment area is greater than the preset threshold, the exploration point is considered a favorable shale oil enrichment area; otherwise, the exploration point is not considered a favorable shale oil enrichment area.

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