Low-permeability lithologic reservoir porosity pressure correction evaluation method

Abstract

The present application belongs to the technical field of petroleum geological exploration, and specifically provides a low-permeability lithologic reservoir porosity overburden correction evaluation method, comprising the following steps: collecting cores, and establishing a porosity overburden change state equation; obtaining triaxial porosity through the porosity overburden change state equation and the net overburden pressure of core burial depth, converting the triaxial porosity into corrected formation porosity using a correction formula, fitting the corrected formation porosity and surface porosity, obtaining a corrected formation porosity and surface porosity fitting formula, and determining and evaluating reservoir porosity according to the corrected formation porosity and surface porosity fitting formula. The present application solves the problems of the existing core collection not being representative, large evaluation error of effective thickness reservoir, large error in formation porosity determination, and low evaluation quality; the cores collected by the present application are highly representative, the evaluation quality of effective thickness reservoir is high, and the determination and evaluation quality of formation porosity is high.

Description

Technical Field

[0001] This invention belongs to the field of petroleum geological exploration technology, specifically relating to a method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs. Background Technology

[0002] Overburden pressure is one of the main factors affecting reservoir properties. Research on the porosity and permeability characteristics of overburden pressure is of great significance for reserve calculation, reservoir evaluation, and exploration, development, and production of low-porosity, low-permeability reservoirs. The results of this research can be directly applied to relevant reserve calculations, ensuring more reliable and accurate results that meet reserve specifications. Furthermore, the research findings can serve as a primary basis for effective reservoir evaluation, laying the foundation for in-depth research on reservoir fracturing and horizontal well development design, and directly serving exploration, development, and production.

[0003] The study of the changes in physical properties due to overburden was conducted abroad as early as the 1940s.

[0004] Chinese patent document CN105184034A, published on December 23, 2015, discloses a method for correcting the overburden properties of shale reservoirs, belonging to the field of oil and gas exploration. Based on reservoir core overburden tests, this document establishes reservoir property overburden correction models by analyzing the relationship and law between the changes in physical properties after core overburden and the changes in overburden pressure, namely, reservoir porosity overburden correction models and reservoir permeability overburden correction models. The method includes the following steps: (1) conducting core overburden tests and obtaining experimental results; (2) establishing core property overburden correction models: based on the experimental results obtained in step (1), analyzing the relationship between the changes in core overburden property values ​​and overburden values, and establishing a relationship model between the overburden properties and overburden value changes of each core sample; (3) establishing reservoir property overburden correction models: analyzing the differences between the various core property overburden correction models established in step (2), and the variation law between the differences and the magnitude of conventional physical property values ​​of the core surface. However, this paper also fails to address the existing technical methods, which suffer from the following problems:

[0005] 1) The core samples collected during core sampling are not representative, which affects the quality of subsequent evaluation;

[0006] 2) During the evaluation, non-effective thickness samples are not removed, resulting in a large error in the evaluation results for reservoirs with effective thickness;

[0007] 3) Overburden pressure value during the experiment: The original technique used 1 / 2 of the overburden pressure value. However, this value cannot simulate the actual formation pressure, resulting in errors in the experimental formation porosity measurement.

[0008] 4) The porosity data is mainly obtained by testing conventional physical properties using the kerosene method. The results obtained by this method do not conform to the porosity of natural gas reservoirs, which ultimately leads to the distortion of experimental data and affects the evaluation results. Summary of the Invention

[0009] The purpose of this invention is to overcome the problems existing in the prior art regarding the porosity overburden correction evaluation method for low-permeability lithologic reservoirs.

[0010] Therefore, the present invention provides a method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs, comprising the following steps:

[0011] 1) Collect core samples based on the rock type and cementation characteristics of the target strata in the region. The core samples should cover all reservoir rock types and cementation characteristics in the target region.

[0012] 2) Under laboratory conditions, simulate actual formation pressure and determine core porosity under different formation pressure conditions; and at the beginning of the experiment, measure the surface core porosity; the core porosity under different formation pressure conditions is the formation core porosity; the pressure value of the formation pressure is the net overburden pressure of the reservoir.

[0013] 3) Establish a state equation for porosity overburden variation based on the measured overburden pressure, formation core porosity, and surface core porosity;

[0014] 4) Determine the net overburden pressure at the core burial depth. Obtain the triaxial porosity using the porosity overburden pressure change state equation and the net overburden pressure at the core burial depth. Use a correction formula to convert the triaxial porosity into corrected formation porosity. Fit the corrected formation porosity with the formation porosity to obtain the corrected formation porosity and formation porosity fitting formula. Determine and evaluate reservoir porosity based on the corrected formation porosity and formation porosity fitting formula.

[0015] Preferably, in step 2), the core porosity under different formation pressure conditions is determined using the kerosene method and the helium method; and the core porosity determined by the kerosene method and the core porosity determined by the helium method are fitted to obtain a conversion chart established by the kerosene method and the helium method.

[0016] Preferably, the helium method in step 2) is used to test the gas reservoir.

[0017] Preferably, when testing the gas reservoir, if the kerosene method is used to determine the core porosity, the core porosity determined by the kerosene method is converted into the core porosity determined by the helium method using a conversion chart established by the kerosene method and the helium method.

[0018] Preferably, the state equation for the porosity overburden change in step 3) is expressed as a binomial.

[0019] Preferably, the state equation for the porosity overburden variation is as follows: Where a and b are fitting coefficients; Φ o Φ represents the porosity of ground core samples. eff P represents the porosity of the formation core. eff This represents the net overburden of the reservoir.

[0020] Preferably, in step 4), the formula for converting triaxial porosity into corrected formation porosity using the correction formula is: Φ f =Φ o -(Φ o -Φ3)ε; where: Φ f - Corrected formation porosity, %; Φ o - Surface core porosity, %; Φ3 - triaxial porosity, %; ε - conversion factor, taken as 0.619.

[0021] Preferably, the porosity of the ground core in step 4) is calculated using the porosity overburden change state equation.

[0022] Preferably, in step 4), when fitting the corrected formation porosity and the ground porosity, layer points outside the effective thickness range are eliminated.

[0023] Preferably, in step 2), when simulating actual formation pressure, the highest experimental pressure is set as the net overburden pressure under the original state of the actual reservoir.

[0024] The beneficial effects of this invention are:

[0025] 1) The porosity overburden correction evaluation method for low-permeability lithologic reservoirs provided by this invention collects core samples based on the rock type and cementation characteristics of the target layer in the region. The core samples are required to cover all reservoir rock types and cementation characteristics in the target area. The collected core samples are representative, and the number of core samples collected is also specified. In this way, the collected core samples can more accurately represent the characteristics of the regional reservoirs, thereby laying a material basis for subsequent evaluation.

[0026] 2) The porosity overburden pressure correction evaluation method for low-permeability lithologic reservoirs provided by this invention measures core porosity under different formation pressure conditions using both the kerosene method and the helium method. This solves the problem that the kerosene method is unsuitable for measuring gas reservoirs, improving the accuracy of measurement data and evaluation results. Even if a gas reservoir is measured using the kerosene method, the conversion chart established by this invention using the kerosene and helium methods can convert the formation core porosity measured by the kerosene method into that measured by the helium method, avoiding rework and facilitating practical application.

[0027] 3) The porosity overburden correction evaluation method for low-permeability lithologic reservoirs provided by this invention eliminates layers outside the effective thickness range when fitting the corrected formation porosity to the surface porosity. This makes the evaluation method more consistent with practical work.

[0028] 4) The porosity overburden pressure correction and evaluation method for low-permeability lithologic reservoirs provided by this invention sets the highest experimental pressure to the net overburden pressure under the original state of the actual reservoir when simulating actual formation pressure. Increasing the pressure can represent the actual situation of the gas reservoir. Attached Figure Description

[0029] The present invention will now be described in further detail with reference to the accompanying drawings.

[0030] Figure 1 This is a diagram showing the distribution range of physical properties of the collected samples;

[0031] Figure 2 It is the curve of porosity variation coefficient versus effective pressure variation using the "five-point method";

[0032] Figure 3 It is the curve of porosity variation coefficient versus effective pressure variation using the "seven-point method";

[0033] Figure 4 These are porosity compressibility curves for typical rock samples from the study area.

[0034] Figure 5 This is a graph showing the variation coefficient of porosity under overburden pressure in different types of sandstone;

[0035] Figure 6 This is a graph showing the relationship between the average porosity compressibility coefficient and the quartz particle content.

[0036] Figure 7 This is a graph showing the relationship between the average porosity compressibility coefficient and the content of argillaceous rock fragments.

[0037] Figure 8 This is a graph showing the relationship between the average porosity compressibility coefficient and the ratio of quartz to clay content;

[0038] Figure 9 This is a graph showing the relationship between the average porosity compressibility coefficient and the median radius;

[0039] Figure 10 This is a graph showing the relationship between the average porosity compressibility coefficient and the maximum pore throat radius;

[0040] Figure 11 This is a graph showing the relationship between average porosity compressibility and median radius;

[0041] Figure 12 This is a graph showing the relationship between average porosity compressibility and maximum pore throat radius;

[0042] Figure 13This is a graph showing the relationship between the average porosity compressibility coefficient and the sorting coefficient.

[0043] Figure 14 This is a graph showing the relationship between average porosity compressibility and skewness.

[0044] Figure 15 This is a graph showing the relationship between average porosity compressibility and sorting coefficient.

[0045] Figure 16 This is a graph showing the relationship between average porosity compressibility and skewness.

[0046] Figure 17 It is a curve showing the change between the average porosity compressibility coefficient and the initial porosity.

[0047] Figure 18 It is a curve showing the change in average porosity compressibility versus initial porosity.

[0048] Figure 19 This is a typical sample porosity versus effective pressure graph;

[0049] Figure 20 This is a graph showing the fitting coefficients of the porosity state equation;

[0050] Figure 21 This is a graph showing the relationship between the fitting coefficient 'a' of the porosity equation of state and the physical properties.

[0051] Figure 22 This is a graph showing the relationship between the fitting coefficient b of the porosity equation of state and physical properties.

[0052] Figure 23 A comparative chart of porosity test results of Taiyuan Formation sandstone in Shenmu area using helium and kerosene methods;

[0053] Figure 24 This is a comparison chart of porosity test results under surface and strata conditions of the Taiyuan Formation sandstone in the Shenmu area.

[0054] Figure 25 This is a comparison chart of porosity test results under surface and strata conditions of the Taiyuan Formation sandstone after initial optimization;

[0055] Figure 26 It is a comparative chart of porosity test results under optimized experimental design and ground and formation conditions;

[0056] Figure 27 This is a flowchart of the present invention. Detailed Implementation

[0057] Example 1:

[0058] like Figure 27 As shown, a method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs includes the following steps:

[0059] 1) Collect core samples based on the rock type and cementation characteristics of the target strata in the region. The core samples should cover all reservoir rock types and cementation characteristics in the target region.

[0060] 2) Under laboratory conditions, simulate actual formation pressure and determine core porosity under different formation pressure conditions; and at the beginning of the experiment, measure the surface core porosity; the core porosity under different formation pressure conditions is the formation core porosity; the pressure value of the formation pressure is the net overburden pressure of the reservoir.

[0061] 3) Establish a state equation for porosity overburden variation based on the measured overburden pressure, formation core porosity, and surface core porosity;

[0062] 4) Determine the net overburden pressure at the core burial depth. Obtain the triaxial porosity using the porosity overburden pressure change state equation and the net overburden pressure at the core burial depth. Use a correction formula to convert the triaxial porosity into corrected formation porosity. Fit the corrected formation porosity with the formation porosity to obtain the corrected formation porosity and formation porosity fitting formula. Determine and evaluate reservoir porosity based on the corrected formation porosity and formation porosity fitting formula.

[0063] The core samples collected in this invention are representative, and the quantity of core samples collected is also specified. In this way, the collected core samples can more accurately represent the characteristics of the regional reservoir, thus laying a material basis for subsequent evaluation. Compared with existing technologies, the reservoir porosity calculated by the low-permeability lithologic reservoir porosity correction evaluation method of this invention is more accurate, and its consistency can reach more than 98%.

[0064] Preferably, in step 2), the core porosity under different formation pressure conditions is determined using the kerosene method and the helium method; and the core porosity determined by the kerosene method and the core porosity determined by the helium method are fitted to obtain a conversion chart established by the kerosene method and the helium method.

[0065] In practical applications, after determining the core porosity using the kerosene method, the porosity determined by the kerosene method can be converted into the porosity determined by the helium method, which is more consistent with the actual situation, using the conversion chart established by this invention for the kerosene method and the helium method.

[0066] Preferably, the helium method in step 2) is used to test the gas reservoir.

[0067] Preferably, when testing the gas reservoir, if the kerosene method is used to determine the core porosity, the core porosity determined by the kerosene method is converted into the core porosity determined by the helium method using a conversion chart established by the kerosene method and the helium method.

[0068] This invention solves the problem that the kerosene method is unsuitable for gas reservoir determination, improving the accuracy of measurement data and evaluation results. Even if the kerosene method is used to determine the gas reservoir, the conversion chart established by the present invention for the kerosene and helium methods can convert the core porosity determined by the kerosene method into the core porosity determined by the helium method, avoiding rework and facilitating practical application.

[0069] Preferably, the state equation for the porosity overburden change in step 3) is expressed as a binomial. Based on the experimental data of this invention, this equation should be expressed as a binomial, as it has the best correlation.

[0070] Preferably, the state equation for the porosity overburden variation is as follows: Where a and b are fitting coefficients; Φ o Φ represents the porosity of ground core samples. eff P represents the porosity of the formation core. eff This represents the net overburden of the reservoir.

[0071] Preferably, in step 4), the formula for converting triaxial porosity into corrected formation porosity using the correction formula is: Φ f =Φ o -(Φ o -Φ3)ε; where: Φ f - Corrected formation porosity, %; Φ o - Surface core porosity, %; Φ3 - triaxial porosity, %; ε - conversion factor, taken as 0.619.

[0072] Preferably, the surface core porosity in step 4) is calculated using the porosity overburden variation state equation. This improves the accuracy of the determined reservoir porosity.

[0073] Preferably, in step 4), when fitting the corrected formation porosity and the formation porosity, layer points outside the effective thickness range are eliminated. This makes the evaluation method more consistent with actual work.

[0074] Preferably, in step 2), when simulating actual formation pressure, the highest experimental pressure is set to the net overburden pressure under the original state of the actual reservoir. Increasing the pressure can better represent the actual situation of the gas reservoir.

[0075] Example 2:

[0076] A method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs includes the following steps:

[0077] 1. Collect core samples based on the rock type and cementation characteristics of the target strata in the region. The core samples should cover all reservoir rock types and cementation characteristics in the target region.

[0078] The target area contains three wells: Shuang125, Shuang127, and Shuang139. The rock types in these three wells include lithic quartz sandstone, lithic sandstone, and argillaceous lithic sandstone. Based on the rock types and cementation characteristics of the three wells, 107 samples were collected, covering all reservoir rock types and cementation characteristics. These 107 samples are representative because they encompass both rock types and cementation characteristics, including rock composition, physical property distribution, and pore structure. Figure 1 ).

[0079] 2. Under laboratory conditions, simulate actual formation pressure and determine core porosity under different formation pressure conditions; and at the beginning of the experiment, measure the surface core porosity; the core porosity under different formation pressure conditions is the formation core porosity; the formation pressure value is the net overburden pressure of the reservoir;

[0080] 2.1 Under laboratory conditions, simulating actual formation pressure, the core porosity under different formation pressure conditions was measured. The specific implementation method is as follows:

[0081] 2.1.1 During the experiment, select the experimental equipment:

[0082] Choose the world-leading AP-608 overburden pressure porosity and permeability tester. The AP-608 is a research instrument developed and continuously improved by Coretest, Inc. based on years of dedicated research and user feedback. It is used in the laboratory to simulate gas reservoir pressure conditions to study the porosity and permeability properties of rock cores. The AP-608 uses the gas pulse attenuation method for measurement, and can measure the gas phase permeability and porosity of rocks under real gas reservoir pressure conditions. It has the following outstanding features:

[0083] ① The system design adopts the most advanced technology currently available, meeting the requirements of specialized, sophisticated, technology-intensive, and low-carbon equipment functions.

[0084] ② All parts and electronic components undergo rigorous quality screening and use the patented Hasler core holder. Due to the special holder design, porosity testing can also be completed under overburden pressure.

[0085] ③ Porosity and pore volume testing adopted Boyles' law. The entire permeability testing process was automated. All collected data, including raw test data, were stored in ASCII files for easy viewing at any time.

[0086] ④ Measurable parameters include equivalent liquid permeability, gas permeability under overburden pressure, slip factor b, inert parameters β and α, pore volume and porosity under overburden pressure.

[0087] 2.1.2 Determine the experimental method:

[0088] Core porosity under different formation pressure conditions was determined using the kerosene method and the helium method; and the core porosity determined by the kerosene method and the core porosity determined by the helium method were fitted to obtain a conversion chart established by the kerosene method and the helium method.

[0089] The experiment that measures the core porosity under different formation pressure conditions is a conventional porosity calibration chart experiment.

[0090] The main purpose of this stage of the experiment is to meet the requirements for establishing porosity correction charts. This experiment has the following characteristics:

[0091] Because the requirements of the industry standard "Core Analysis Methods" SYT 5336-2006 were strictly followed, the porosity and permeability analysis of 53 blocks under the helium method was designed and completed, laying the foundation for the establishment of porosity correction charts under the conventional kerosene method and the helium method (the results are shown in Table 1).

[0092] Table 1 Summary of physical property test results under conventional kerosene method and helium method

[0093]

[0094]

[0095] Following strict adherence to the industry standard SYT 6385-1999, "Methods for Determining Porosity and Permeability of Rocks Under Overburden," porosity analysis was designed and completed for 30 samples under overburden conditions. This not only laid the foundation for establishing porosity calibration charts under overburden conditions but also for preliminary analysis and in-depth research on the laws governing property changes. To ensure that the sample design met the requirements for establishing porosity calibration charts, the sample properties were selected to be representative, covering the main property distribution ranges of the target strata in the study area. Specifically, the porosity ranged from 3.5% to 12.7%, and the permeability ranged from 0.04 mD to 4.07 mD. The lithologies included lithic quartz sandstone, lithic sandstone, and argillaceous lithic sandstone, among other major rock types.

[0096] Helium-kerosene porosity correction chart

[0097] Porosity and permeability data are mainly obtained through kerosene testing for conventional physical properties. To simulate the porosity of natural gas reservoirs, it is necessary to convert the porosity measured by the conventional kerosene method to that measured under helium conditions. Porosity analysis results from 53 samples under helium conditions show that the overall porosity measured under helium conditions is larger than that measured by the conventional kerosene method (Table 1). Based on the analysis of these 53 samples, a calibration chart was established by fitting the porosity analysis results of 46 representative samples under helium conditions with the porosity results measured by the conventional kerosene method. The chart analysis results show that, overall, the porosity under helium conditions is 0.4% larger than that under kerosene conditions (…). Figure 23 ).

[0098] 2.1.3 The experimental method for determining core porosity under different formation pressure conditions includes the following steps:

[0099] ① Determine the highest experimental confining pressure

[0100] Based on the sampling depth of the study area, which ranges from 2387m to 2470m, and the average density of the overlying strata generally taken as 2.3 g / cm³, the calculated overlying rock pressure is between 53.8 MPa and 55.8 MPa. In accordance with the requirements of SYT 6385-1999, "Methods for Determining Porosity and Permeability of Rocks Under Overlying Pressure," the maximum experimental confining pressure is selected based on half of the overlying rock pressure, thus the maximum confining pressure is chosen to be between 27.8 MPa and 26.9 MPa.

[0101] ② Keep the import pressure value unchanged

[0102] While keeping the inlet pressure constant, the confining pressure was slowly increased so that the net effective pressure was approximately 3.45, 6.9, 13.79, 20.69, and 27.59 MPa respectively. The pressure was maintained at each point until it stabilized, and the gas porosity of the rock sample was measured. The results are shown in Table 2.

[0103] Table 2 Summary of Porosity Correction Experiment Results Using the Five-Point Method under Increased Confining Pressure

[0104]

[0105]

[0106] 2.1.4 Experimental method for simulating the original net pressure porosity of the reservoir:

[0107] According to Terzaghi's effective stress theory, the original net pressure of a reservoir refers to the difference between the pressure of the overlying strata and the original pore pressure of the reservoir. Based on a systematic analysis of porosity test data from 30 conventional overlying pressure test blocks, and considering that the actual original static pressure of the reservoir is much greater than half of the overlying pressure, a simulated original net pressure porosity experiment was designed to further the research. The specific experimental procedure was carried out in accordance with the "Method for Determining the Compressibility Coefficient of Rock Pores" SY / T5815-2008. The specific steps are as follows:

[0108] (1) Determine the initial static overburden pressure

[0109] Based on the target layer burial depth and the average density of the overlying strata, the rock pressure of the overlying strata is calculated to be between 53.8 MPa and 55.8 MPa. According to the regression relationship between gas well test pressure and altitude, the fluid pressure of the gas reservoir in the study area is calculated to be around 21 MPa to 22.5 MPa. Based on this, the initial static effective pressure is calculated to be between 32 MPa and 34 MPa.

[0110] (2) Keep the import pressure value unchanged.

[0111] Eleven representative core samples were selected. While keeping the inlet pressure constant, the confining pressure was slowly increased so that the net effective pressure was approximately 5, 10, 15, 20, 25, 30, and 35 MPa. The pressure was maintained at each point until it stabilized, and the gas porosity of the rock samples was measured (Table 3).

[0112] Table 3 Summary of Porosity Experiment Results Using the Seven-Point Method under Increased Confining Pressure

[0113]

[0114] (3) Decrease the net effective pressure in sequence

[0115] These 11 rock samples were then subjected to a series of reductions in net effective pressure, with the pressure decreasing at 35, 30, 25, 20, 15, 10, and 5, and each pressure point was maintained until it stabilized. The gas porosity values ​​of the rock samples after the pressure reduction were then measured (Table 4).

[0116] (4) Other supporting experiments

[0117] Based on the research needs and the collection of extensive basic analytical data from the study area, we completed the analysis of 13 thin-section castings and 9 mercury porosimetry samples.

[0118] Table 4 Summary of porosity test results using the "seven-point method" under reduced confining pressure.

[0119]

[0120] 2.1.5 Experimental parameters and result analysis:

[0121] 2.1.5.1 Porosity Variation Law

[0122] This experiment completed porosity analysis on a large number of samples under overburden conditions, laying the foundation for establishing the variation law of overburden porosity.

[0123] Porosity variation coefficient (Φ / Φ) o The porosity is defined as the ratio of porosity under overburden conditions to the initial point porosity. This is derived from the established relationship between the porosity variation coefficient and the net effective pressure. Figure 2 , Figure 3 It can be seen that as the net effective pressure increases, the porosity variation coefficient decreases significantly and steeply in the early stages, gradually slowing down as the net effective pressure increases, but the variation range varies among different core samples. From the initial pressure of 3.5 MPa to the maximum net effective pressure of 27.5 MPa, the variation coefficient ranges from 0.4 to 0.9.

[0124] 2.1.5.2 Determination of Key Analytical Parameters

[0125] The above analysis of the variation patterns shows that the porosity variation coefficient of the analyzed samples varies under different initial points and other conditions. In order to compare and analyze samples under different conditions, the following key parameters need to be established.

[0126] (1) Porosity compressibility coefficient

[0127] In determining the key parameters, the concept of pore volume compressibility coefficient was referenced from the standard SY / T5818-2008, "Method for Determining the Pore Volume Compressibility Coefficient of Rocks". The pore volume compressibility coefficient is an important indicator for studying changes in reservoir porosity and is also significant in evaluating the elastic productivity of gas reservoirs and calculating dynamic geological reserves. It differs from the rock compressibility coefficient in that the former uses pore volume as the basis, while the latter uses the surface volume of the rock as the basis. The pore volume compressibility coefficient refers to the change in unit pore volume when the pressure changes.

[0128] Based on this, the porosity compressibility coefficient is defined as the change in porosity when the unit pressure is changed.

[0129]

[0130] In the formula: C p - Rock porosity compressibility coefficient, expressed in megapascals (MPa). -1 );Φ p - The porosity value at each effective pressure, in %; dΦ p / dp - A numerical value indicating the change in porosity per unit pressure, expressed as a percentage per megapascal (% / MPa). -1 ).

[0131] ① Based on the experimental results, net effective pressure was selected as the X-axis and porosity as the Y-axis for fitting. Based on the fitting results, the curve equation with the best correlation was selected as the fitting equation.

[0132] ② Select the porosity at the zero pressure point as the original porosity value.

[0133] ③ Calculate the porosity and dΦ at each effective pressure using the selected fitting equation. p / dp value.

[0134] ④ Calculate the rock porosity compressibility coefficient under effective pressure according to formula (1-1).

[0135] (2) Porosity compressibility curve

[0136] The porosity compressibility curves of typical rock samples from the study area show that ( Figure 4As the effective pressure increases, the compressibility coefficient of different core samples shows a significant decreasing trend. Specifically, with the increase of effective pressure, the compressibility coefficient initially decreases relatively quickly, but the decrease in porosity coefficient slows down after the effective pressure increases to 30 MPa. This is because: initially, the rock skeleton is relatively loose, and with the increase of effective pressure, the compaction effect is more obvious, resulting in a rapid decrease in the rock compressibility coefficient; as the effective pressure continues to increase, the space available for compression in the rock sample decreases, and the decrease in the rock compressibility coefficient tends to level off.

[0137] The overall variation pattern of porosity compressibility coefficients in samples of different lithologies in the study area is similar, but the variation range varies among different samples. The study shows that porosity compressibility coefficient is a binary function of rock skeleton hardness and porosity. Under the same rock skeleton, high porosity results in high compressibility, while low porosity results in low compressibility. Furthermore, under the same porosity, soft rocks are more easily compressible.

[0138] (3) Average porosity compressibility coefficient

[0139] To characterize the differences in the compressibility rate of different samples and reflect the overall difference in pore volume compression from the ground (or initial point) to the original net effective pressure of the formation (or under the maximum test pressure), the concept of average porosity compressibility coefficient is introduced based on the porosity compressibility coefficient. Wherein, Φ P Select the porosity at zero-point pressure (or initial-point pressure), dΦ p The / dp value is the result calculated from the ground (or initial point) to the original net effective pressure of the formation (or under the maximum test pressure) (Table 5).

[0140] Table 5. Calculation of Average Porosity and Compressibility Coefficient of Typical Samples

[0141]

[0142] (4) Average porosity compression

[0143] To describe the differences in compression changes among different samples and to reflect the average compression of samples under a unit pressure drop, the concept of average porosity compressibility is introduced. It is defined as the change in porosity compressibility under a unit pressure difference. In this study, the analysis mainly focuses on the overall compression change of samples from the ground (or initial point) to the original net effective pressure of the formation (or under the maximum test pressure). Table 6 shows the calculated results of average porosity compressibility for typical samples from the initial point to the original state of the formation.

[0144] Table 6. Calculation of Average Porosity Compressibility for Typical Samples

[0145]

[0146] 2.1.5.3 Analysis of Factors Affecting Porosity Variation

[0147] The change in porosity with overlying pressure is affected by a variety of factors, including the composition of the rock skeleton, the type of cement, the pore structure and physical properties of the rock. The porosity of rocks with different properties changes to different extents with the increase of net overlying pressure.

[0148] 2.1.5.4 Rock type and cement type

[0149] from Figure 5 It can be noted that the variation in porosity among the three different rock types with net overlying rock pressure varies significantly. Among them, the porosity variation in lithic quartz sandstone is the smallest, while that in mudstone-bearing lithic sandstone is the largest. The average porosity compressibility coefficient is directly proportional to its quartz grain content and inversely proportional to its mudstone content. Figure 6 , Figure 7 When the content of argillaceous rock fragments increased from 6% to 17%, the average porosity compressibility coefficient increased from 33 × 10⁻⁶ to 17%. -4 MPa -1 Increased to 54×10 -4 MPa -1 When the quartz particle content decreased from 80% to 60%, the average porosity compressibility coefficient decreased from 33 × 10⁻⁶. -4 MPa -1 Increased to 54×10 -4 MPa -1 The reason for this is that argillaceous rock fragments are relatively easy to compress, while quartz grains have strong compressive strength. Therefore, the higher the quartz content and the lower the argillaceous rock fragment content, the stronger the rock's compressive strength. Figure 8 ).

[0150] 2.1.5.5 Pore Structure Characteristics

[0151] Besides reservoir lithology and cementation characteristics, the pore structure of rocks also affects the compressibility of pore volume. The pore structure of a rock refers to the geometry, size, distribution, and interconnectivity of its pores and throats. Currently, mercury intrusion porosimetry is the most commonly used method to describe pore-throat structure characteristics. Not only can the morphology of capillary pressure curves reveal the pore structure characteristics of reservoir rocks, but quantitative descriptions of these curves can also effectively demonstrate the influence of pore structure on the variation characteristics of overburden porosity.

[0152] The first category consists of parameters that quantify pore throat size, including the maximum pore throat radius and the median radius. The maximum pore throat radius refers to the throat corresponding to the point where the non-wetting phase begins to enter the rock sample, which is the radius of the largest connected pore throat corresponding to the threshold pressure. The median radius, also known as the median throat radius, refers to the throat radius corresponding to 50% saturation on the displacement capillary pressure curve; the larger this value, the larger the pore throat radius of the rock sample, and the relatively better its permeability.

[0153] The second category consists of parameters representing pore throat sorting characteristics, including the sorting coefficient, coefficient of variation, and skewness coefficient. The sorting coefficient reflects the concentration of throat size distribution, describing the degree of dispersion centered on the mean; a smaller sorting coefficient indicates better pore sorting. The coefficient of variation describes the comparison between the average pore size and the degree of sorting, reflecting the quality of the pore structure; generally, a larger value indicates a better pore structure. The skewness coefficient is one of the distribution characteristic parameters; it is a measure of asymmetric distribution, also known as skewness. A value less than 0 indicates fine skewness, and a value greater than 0 indicates coarse skewness. To study the relationship between pore structure characteristics and porosity variation under overburden pressure, the average porosity compressibility coefficient and average porosity compressibility from the surface to the formation were calculated for each experimental sample.

[0154] from Figures 9-12 It can be seen that the median radius of typical reservoir samples in the study area ranges from 0.1 μm to 0.75 μm, while the maximum pore throat radius ranges from 0.6 μm to 2.8 μm. The average porosity compressibility coefficient of the reservoir is generally negatively correlated with the median and maximum pore throat radii of the sandstone reservoirs in the study area, while the average porosity compressibility is generally positively correlated with both pore throat radii. In other words, the smaller the pore throat, the greater the average porosity compressibility coefficient tends to be, but the smaller the porosity compressibility. This is mainly because the lithology of the study area controls the physical properties; when the quartz grain content is high, larger pore throats are generally retained. Because the quartz content is high, the porosity compressibility coefficient is actually lower. However, the larger the porosity, the larger the compressible space, thus the greater the average porosity compressibility.

[0155] from Figures 13-16 It can be seen that the porosity sorting coefficient of typical reservoirs in the study area ranges from 1.5 to 2.7, the coefficient of variation ranges from 0.12 to 0.24, and the skewness ranges from -0.3 to 0.6. The average porosity compressibility coefficient of the reservoir is negatively correlated with both the sorting coefficient and the skewness. The average porosity compressibility of the reservoir is positively correlated with both the sorting coefficient and the skewness. This indicates that better sorting and finer skewness result in a larger compressibility coefficient but a smaller compressibility.

[0156] 2.1.5.6 Analysis of the Influence of Physical Properties

[0157] The graph comparing the average porosity compressibility coefficient and average porosity compressibility with the initial porosity value from the initial point of the experiment to the maximum net effective stress clearly shows... Figure 17 , Figure 18Although a larger initial porosity results in a smaller average porosity compressibility coefficient, the average porosity compression of samples with larger initial porosity is still relatively large. This is related to the fact that porosity compression is influenced by both rock properties and the initial porosity. The porosity compressibility coefficient is mainly controlled by lithology, while the porosity compression generally reflects physical property factors. Since lithology in the study area has a certain controlling effect on physical properties, reservoirs with high quartz grain content and low argillaceous rock fragment content generally retain larger porosity, while those with high argillaceous content and low quartz grain content have lower porosity.

[0158] 3. Establish a state equation for porosity overburden variation based on the measured overburden pressure, formation core porosity, and surface core porosity;

[0159] (1) Establish the state equation for porosity overburden variation

[0160] Through multi-parameter (including porosity and overburden pressure, porosity ratio and overburden pressure, porosity difference and overburden pressure, etc.) and multi-method regression comparative analysis (including linear, logarithmic, binomial, power, and exponential), the binomial expression showed the best correlation between porosity and net pressure under overburden pressure conditions in the study area. Figure 19 Based on this, a state equation for porosity overburden variation was established.

[0161]

[0162] Where a and b are fitting coefficients; Φ o Porosity under ground conditions; Φ eff Porosity under effective pressure; P eff This represents the net effective pressure. The fitting results show that the correlation coefficients of all curves are greater than 0.99, indicating a very good curve fit.

[0163] This experiment completed porosity analysis on a large number of samples under overburden conditions, laying the foundation for establishing the state equation for porosity changes under overburden conditions.

[0164] (2) Analysis of the relationship between the fitting coefficients of the state equation and physical properties

[0165] Table 7 is a statistical table of typical curve fitting coefficients. By selecting typical curves for the study area and combining them with lithology, physical properties, and pore structure analysis, it is concluded that the fitting coefficients a and b are highly correlated and closely related to the physical properties at the initial point.

[0166] from Figure 20 It can be seen that the fitting coefficients a and b have a power-law relationship, and the correlation coefficient is high. The square root of the product of the fitting coefficients a and b with the initial point pore permeability has a good correlation, and both show logarithmic correlation. Figure 21 , Figure 22 This lays the foundation for obtaining the equation of state for the change of overburden porosity under certain conditions using initial physical properties.

[0167] Table 7 Summary of Fitting Coefficients for Porosity Equation of State

[0168] hashtag Sample number a b <![CDATA[Φ0(%)]]> <![CDATA[K0(mD)]]> <![CDATA[(Φ0×K0) 1 / 2 ]]> Double 139 75 0.001 0.0791 10.941 0.481 2.294 Double 127 32 0.0011 0.0787 8.539 0.562 2.191 Double 127 75 0.0013 0.0868 11.527 3.003 5.884 Double 127 46 0.0008 0.0671 9.469 1.668 3.974 Double 127 101 0.001 0.0699 6.736 0.146 0.992 Double 127 118 0.0012 0.0776 7.687 0.119 0.956 Double 127 149 0.0009 0.0601 4.488 0.075 0.580 Double 127 169 0.0007 0.0566 5.34 0.082 0.662 Double 127 185 0.0008 0.0587 4.933 0.077 0.616 Double 127 184 0.0005 0.0415 3.729 0.012 0.212 Double 127 39 0.0013 0.084 10.658 2.275 4.924

[0169] 4. Determine the net overburden pressure at the core burial depth. Obtain the triaxial porosity using the porosity-overburden pressure variation state equation and the net overburden pressure at the core burial depth. Transform the triaxial porosity into corrected formation porosity using a correction formula. Fit the corrected formation porosity to the formation porosity to obtain a corrected formation porosity-formation porosity fitting formula. Determine and evaluate reservoir porosity based on this corrected formation porosity-formation porosity-formation porosity fitting formula. The specific implementation method is as follows:

[0170] 4.1. Determine the net overburden pressure value based on the burial depth of the sample. Substitute the determined net overburden pressure value into the fitted porosity overburden pressure change state equation to obtain the overburden pressure porosity of the sample. This porosity is the triaxial porosity.

[0171] Since the measurement experiment was completed in accordance with the requirements of SYT 6385-1999 "Methods for Determining Porosity and Permeability of Rocks Under Overburden", and by fitting the experimental results using various methods, the quadratic equation with univariate was found to have the highest fitting accuracy, with a correlation coefficient above 0.99.

[0172] 4.2. Using the formula in SYT 6385-1999, "Methods for Determining Porosity and Permeability of Rocks Under Overburden," triaxial porosity is converted into formation porosity. The formula is as follows:

[0173] Φ f =Φ o -(Φ o -Φ3)ε (1-3)

[0174] Where: Φ f - Corrected formation porosity, %; Φ o - Ground core analysis porosity, %; Φ3 - triaxial porosity, %; ε - conversion factor, taken as 0.619.

[0175] 4.3 After calculating the formation porosity of each rock sample (Table 8), the formation porosity of all tested rock samples was fitted with the initial point porosity. According to the experience of the US Core Testing Company, the porosity of rocks changes very little under early overburden pressure. Therefore, in China, the porosity at the initial point of overburden pressure testing is generally used as the formation porosity to develop a formation porosity correction chart. Figure 24Using the aforementioned empirical formula for porosity correction, it can be calculated that the average porosity of the Taiyuan Formation in the Shenmu area is 0.65% greater than that of the formation. However, this chart has certain problems, specifically, the difference between surface porosity and formation porosity varies considerably, ranging from a minimum of only 0.3% to a maximum of 1.59%. Further optimization is necessary.

[0176] Table 8 Summary of Calculation Results of Overburden Porosity

[0177]

[0178]

[0179] Because the average porosity of the Taiyuan Formation sandstone reservoir is relatively low, the accuracy of the porosity correction chart has a significant impact on the accuracy of the reserves. To accurately develop the porosity correction chart, we optimized the experiments and results analysis from the following three aspects, based on conventional experimental analysis.

[0180] Firstly, considering the relatively small porosity of low-permeability areas, to increase the accuracy of the map, the ground porosity is directly obtained through fitting relationships, rather than simply using the initial point porosity to replace the ground porosity.

[0181] Secondly, the porosity correction chart is mainly used in reserve calculation. During chart creation, non-effective thickness layers should be eliminated. Based on this, 30 test samples were optimized into 18 layers within the effective thickness range for reserve calculation (Table 9). After the above optimization and fitting, the difference between formation porosity and surface porosity ranged from 0.71% to 0.98%, with an average difference of 0.86% for the samples. Furthermore, it generally conforms to the characteristic that larger porosity leads to greater compression, and smaller porosity leads to less compression. Figure 25 ).

[0182] Table 9 Summary of Calculation Results for Optimized Overburden Porosity

[0183]

[0184]

[0185] Third, the experimental design was optimized, exceeding the requirements of SYT 6385-1999, "Methods for Determining Porosity and Permeability of Rocks Under Overburden Pressure." Following Terzaghi's effective stress theory, the maximum experimental pressure was designed to match the net overburden pressure under the original state of the actual gas reservoir. For the study of the target layer, if half of the overburden pressure is used as specified in SYT 6385-1999, the maximum experimental pressure would only be 27.6 MPa, while the net overburden pressure of actual gas reservoirs is between 33 MPa and 35 MPa. Therefore, increasing the pressure allows for a more representative fit of the experimental results to the actual gas reservoir conditions.

[0186] The results of the net overburden pressure experiments on nine samples were fitted and calculated (Table 10). The difference between formation porosity and surface porosity ranged from 0.67% to 0.92%, with an average difference of 0.80% for the samples. Overall, the results showed that higher porosity resulted in greater compression, while lower porosity resulted in less compression. Figure 26 Analysis suggests that the net overburden test results better reflect the actual situation of the gas reservoir and are more representative of overburden correction.

[0187] Table 10 Summary of Experimental Results for Net Coverage Porosity

[0188]

[0189]

[0190] The above examples are merely illustrative of the present invention and do not constitute a limitation on the scope of protection of the present invention. All designs that are the same as or similar to the present invention are within the scope of protection of the present invention.

Claims

1. A method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs, characterized in that: Includes the following steps: S1. Collect core samples based on the rock type and cementation characteristics of the target layer in the region. The core samples are required to cover all reservoir rock types and cementation characteristics in the target region. S2. Under laboratory conditions, simulate actual formation pressure and determine the core porosity under different formation pressure conditions; Furthermore, at the beginning of the experiment, the porosity of the surface core was measured; the core porosity under different formation pressure conditions is the formation core porosity; the pressure value of the formation pressure is the net overburden pressure of the reservoir; when simulating the actual formation pressure in step S2, the highest experimental pressure is set as the net overburden pressure under the original state of the actual reservoir. S3. Establish a state equation for porosity overburden variation based on the measured overburden pressure, formation core porosity, and surface core porosity. S4. Determine the net overburden pressure at the core burial depth. Obtain the triaxial porosity using the porosity overburden pressure change state equation and the net overburden pressure at the core burial depth. Convert the triaxial porosity into corrected formation porosity using a correction formula. Fit the corrected formation porosity with the surface porosity to obtain the corrected formation porosity and surface porosity fitting formula. Determine and evaluate reservoir porosity based on the corrected formation porosity and surface porosity fitting formula. In step S4, when fitting the corrected formation porosity and surface porosity, remove layers outside the effective thickness range.

2. The method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs as described in claim 1, characterized in that: In step S2, the core porosity under different formation pressure conditions is determined using the kerosene method and the helium method; and the core porosity determined by the kerosene method and the core porosity determined by the helium method are fitted to obtain a conversion chart established by the kerosene method and the helium method.

3. The method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs as described in claim 2, characterized in that: In step S2, the helium method is used to test the gas reservoir.

4. The porosity overburden correction and evaluation method for low-permeability lithologic reservoirs as described in claim 3, characterized in that: When testing the gas reservoir, if the kerosene method is used to determine the core porosity, a conversion chart is established between the kerosene method and the helium method to convert the core porosity determined by the kerosene method into the core porosity determined by the helium method.

5. The method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs as described in claim 1, characterized in that: The state equation for the porosity overburden change in step S3 is expressed as a binomial.

6. The method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs as described in claim 1, characterized in that: The equation for the porosity overburden change state is: ;in, , These are the fitting coefficients; Porosity of ground core samples; Core porosity; This represents the net overburden of the reservoir.

7. The method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs as described in claim 1, characterized in that: In step S4, the formula for converting triaxial porosity into corrected formation porosity is as follows: ;in: The corrected formation porosity is % %. The porosity of the ground core is %; Triaxial porosity, % The conversion factor is set to 0.

619.

8. The method for evaluating porosity overburden pressure correction in low-permeability lithologic reservoirs as described in claim 1, characterized in that: The porosity of the ground core in step S4 is calculated using the porosity overburden variation state equation.

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