Method and device for comprehensively evaluating fracturing performance of tight reservoir geological engineering

Abstract

The invention belongs to the technical field of oil and gas exploitation, and particularly discloses a tight reservoir geological engineering fracturing performance comprehensive evaluation method and device.The tight reservoir geological engineering fracturing performance comprehensive evaluation method comprises the steps that multiple evaluation indexes capable of influencing the fracturing performance of a reservoir are obtained through the geological aspect and the engineering aspect; according to the influence degree of each evaluation index on the fracturing performance, constructing an evaluation matrix considering the data of all sounding points on the fracturing section; obtaining the influence relation of each evaluation index on the fracturing performance, and correcting the evaluation matrix according to the influence relation; according to the corrected evaluation matrix, obtaining a distance relationship between each sounding point on the fracturing section and an ideal point, so as to construct a first model for evaluating the fracturing performance; the method has the following advantages that the influence of geological parameters and engineering parameters on the fracturing performance of the reservoir is comprehensively considered, and the fracturing performance of the tight reservoir can be accurately and quantitatively evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploitation, and in particular, to a comprehensive evaluation method and device for the fracturability of a tight reservoir in geological engineering. Background Art

[0002] For the evaluation of the fracturability of the reservoir corresponding to the horizontal well of the fractured well in the tight reservoir, most of them use single-factor quantitative evaluation of the brittleness index or three-parameter comprehensive quantitative evaluation from the engineering perspective in combination with in-situ stress and fracture toughness, lacking multi-factor quantitative calculation research from both the reservoir geology and engineering perspectives. Since it is very difficult to comprehensively quantitatively calculate and characterize a large number of geological factors and engineering factors, usually only single-factor and three-parameter quantitative calculations in engineering are considered, resulting in limited measurement accuracy.

[0003] Therefore, a comprehensive evaluation method and device for the fracturability of a tight reservoir in geological engineering are proposed to solve the above-mentioned problems. Summary of the Invention

[0004] The present invention aims to provide a comprehensive evaluation method and device for the fracturability of a tight reservoir in geological engineering to solve or improve at least one of the above technical problems.

[0005] In view of this, the first aspect of the present invention provides a comprehensive evaluation method for the fracturability of a tight reservoir in geological engineering.

[0006] The second aspect of the invention provides a comprehensive evaluation device.

[0007] The third aspect of the present invention provides an electronic device.

[0008] The fourth aspect of the present invention provides a computer-readable storage medium.

[0009] The first aspect of the present invention provides a comprehensive evaluation method and device for the fracturability of a tight reservoir in geological engineering. According to the distance relationship between multiple sounding points on the fracturing section in the reservoir and the ideal point, the fracturability is evaluated. The comprehensive evaluation includes the following steps: obtaining multiple evaluation indicators that can affect the fracturability of the reservoir through geological and engineering aspects; constructing an evaluation matrix considering the data of all the sounding points on the fracturing section according to the influence degree of each evaluation indicator on the fracturability; obtaining the influence relationship of each evaluation indicator on the fracturability, and correcting the evaluation matrix according to the influence relationship; obtaining the distance relationship between each sounding point on the fracturing section and the ideal point according to the corrected evaluation matrix to construct a first model for evaluating the fracturability.

[0010] In any of the above technical solutions, the step of obtaining multiple evaluation indicators that can affect the fracturability of the reservoir specifically includes: obtaining the evaluation indicators of continuous geological sweet spots and engineering sweet spots at different depths of the horizontal wellbore of the reservoir; constructing a second model for calculating the fracturability index based on the evaluation indicators of the engineering sweet spots; and using the fracturability index as one of the evaluation indicators for evaluating the fracturability.

[0011] In any of the above technical solutions, the evaluation indicators of the engineering sweet spots considered by the second model include brittleness index, fracture toughness, net pressure, and stress difference; and the second model includes: Wherein, the F rac is the fracturability index, the B rit is the brittleness index, both a and b are weighted coefficients of effective fracture toughness, the K I is the mode-I fracture toughness, the K II is the mode-II fracture toughness, the p net is the net pressure in the fracture, the σ H is the maximum horizontal principal stress, the σ h is the minimum horizontal principal stress, the σ H -σ h is the stress difference.

[0012] In any of the above technical solutions, the step of correcting the evaluation matrix according to the influence relationship specifically includes: obtaining a first correlation relationship between the evaluation indicator and the fracturability in terms of numerical increase and decrease, and correcting each depth point of the current evaluation indicator in the evaluation matrix according to the extreme value of the evaluation indicator and the first correlation relationship; obtaining a second correlation relationship between the evaluation indicator and its optimal parameter in terms of distance, and using the second correlation relationship as a weight to correct the evaluation indicator corresponding to the second correlation relationship in the evaluation matrix.

[0013] In any of the above technical solutions, the step of correcting the data of each depth point of the current evaluation indicator in the evaluation matrix specifically includes: according to the first correlation relationship, if the indicator value of the evaluation indicator is positively correlated with the fracturability, then the current evaluation indicator is a positive ideal indicator; if the indicator value of the evaluation indicator is negatively correlated with the fracturability, then the current evaluation indicator is a negative ideal indicator; the positive ideal indicator is corrected based on the following formula:

[0014] The negative ideal indicator is corrected based on the following formula:

[0015] Replacing the corresponding evaluation indicator in the evaluation matrix with the corrected positive ideal indicator and negative ideal indicator; wherein, the The value corresponding to the i-th sounding point of the j-th evaluation index after correction, where j is the sequence of the corresponding evaluation index, is the maximum value of all sounding points of the fracturing stage corresponding to the j-th evaluation index in the evaluation matrix, is the minimum value of all sounding points of the fracturing stage corresponding to the j-th evaluation index in the evaluation matrix. Here, k is the number of sounding points, m is the last sounding point, and x ij is the value corresponding to the i-th sounding point of the j-th evaluation index before correction.

[0016] In any of the above technical solutions, the step of using the second correlation relationship as a weight to correct the evaluation index corresponding to the second correlation relationship in the evaluation matrix specifically includes: constructing a multi-objective programming model considering the weight of each evaluation index; calculating the attribute weights of the positive ideal index and the negative ideal index respectively according to the second correlation relationship and the multi-objective programming model; performing weighted average processing on the attribute weights, and correcting the evaluation matrix with the processed attribute weights.

[0017] In any of the above technical solutions, the step of obtaining the distance relationship between each sounding point on the fracturing stage and the ideal point according to the corrected evaluation matrix specifically includes: obtaining the ideal value sequence of the ideal point through the corrected evaluation matrix; calculating the Euclidean distance between all evaluation indexes of each sounding point in the fracturing stage and the ideal value sequence; and the first model is specifically the following formula: where, the is the Euclidean distance between the sounding position x oi at the fracturing stage and the positive ideal value, and the is the Euclidean distance between the sounding position x oi at the fracturing stage and the negative ideal value. And the d i (x oi ) is the Euclidean distance between the sounding position x oi at the fracturing stage and the ideal value. And x oi is the sounding corresponding to the i-th sounding point of the fracturing stage, is the value corresponding to in the evaluation matrix after correction.

[0018] The second aspect of the present invention provides a comprehensive evaluation device, comprising: a data collection module for acquiring and storing data of all evaluation indicators that can affect the fracturability of a reservoir; an evaluation indicator screening module for screening the evaluation indicators in terms of geology and engineering according to the influence degree of each evaluation indicator on the fracturability; an evaluation matrix construction module for constructing an evaluation matrix considering all sounding points on a fracturing section; an evaluation matrix correction module for correcting the evaluation matrix according to the relationship between each evaluation indicator and the fracturability; a comprehensive evaluation model construction module for calculating the distance between each sounding point and an ideal point based on the corrected evaluation matrix and the data of the evaluation indicators, and constructing a comprehensive evaluation model for evaluating the fracturability; a visualization and reporting module for generating a visualized evaluation result according to the comprehensive evaluation model and generating an evaluation report.

[0019] The third aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the above method are implemented.

[0020] The fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0021] The beneficial effects of the present invention compared with the prior art:

[0022] Through the method of the present invention, the fracturability of a reservoir can be evaluated quickly and accurately, thereby providing a timely and effective decision-making basis for oil and gas development to improve the decision-making efficiency; combining evaluation indicators in both geology and engineering aspects ensures the comprehensiveness and in-depthness of the evaluation, thereby reducing the evaluation deviation caused by missing key data or indicators; according to different reservoir characteristics and conditions, the evaluation indicators and their weights can be adjusted, making the method have good adaptability; by correcting the evaluation matrix, the method can more truly reflect the actual influence of each indicator on the fracturability, thereby reducing the risk caused by inaccurate evaluation; according to the fracturability results evaluated by the model, resources can be preferentially allocated to areas with high fracturability, thereby improving the economic benefits of oil and gas development; understanding the fracturability of each sounding point can guide the fracturing design and implementation, thereby obtaining better fracturing effects; accurate evaluation can avoid unnecessary tests and development investments and reduce economic losses caused by improper decisions.

[0023] By providing a comprehensive evaluation model for the fracturability of tight reservoirs in geological engineering, which is used to analyze the evaluation problems of the fracturability of geological engineering considering geological parameters such as total hydrocarbon content, gas content, permeability, porosity, and engineering parameters such as brittleness index, fracture toughness, maximum horizontal principal stress, minimum horizontal principal stress, construction displacement, net pressure, etc., and comprehensively considering the influence of geological parameters and engineering parameters on the fracturability of reservoirs, it can accurately and quantitatively evaluate the fracturability of tight reservoirs, bringing significant benefits to the oil and gas industry, including higher decision-making efficiency, more comprehensive evaluation, more accurate results, and more optimized resource allocation, thereby improving the economic benefits of oil and gas exploration and production.

[0024] Additional aspects and advantages of embodiments according to the present invention will become apparent in the following description section, or will be learned through the practice of embodiments according to the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of embodiments in conjunction with the following drawings, in which:

[0026] Figure 1 is a flowchart of the method steps of the present invention;

[0027] Figure 2 is a schematic diagram comparing the gas production of different perforation clusters and the fracturability index of the present invention;

[0028] Figure 3 is a schematic diagram for evaluating sweet spots from a geological perspective of the present invention;

[0029] Figure 4 is a schematic diagram for evaluating sweet spots from an engineering perspective of the present invention;

[0030] Figure 5 is a schematic diagram for evaluating sweet spots from a geological engineering perspective of the present invention;

[0031] Figure 6 is a schematic diagram of the geological, engineering, geological engineering proximity and fracture pressure profiles of the 7th fracturing stage from 2770 to 2860 m in Well Y of the present invention;

[0032] Figure 7 is a schematic diagram of the geological, engineering, geological engineering proximity and fracture pressure profiles of the 9th fracturing stage from 2583 to 2681 m in Well Y of the present invention;

[0033] Figure 8 is a block diagram of the device structure of the present invention;

[0034] Figure 9 is a schematic diagram of the structure of an electronic device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0035] In order to more clearly understand the above objects, features and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0036] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0037] Please refer to Figures 1-9 , and a comprehensive evaluation method and device for the fracturability of a tight reservoir geological engineering in some embodiments of the present invention will be described below.

[0038] As described in the background art, the comprehensive evaluation of fracturability is an important technical means widely used to optimize the fracturing perforation position of horizontal wells to create a complex fracture network and improve the fracturing effect of tight reservoirs. Due to the heterogeneity of geological conditions such as total hydrocarbon content, gas content, permeability, and porosity corresponding to different depth positions along the horizontal well section, the heterogeneity of engineering conditions such as in-situ stress, brittleness index, Young's modulus, Poisson's ratio, and fracture toughness, and the lack of comprehensive quantitative evaluation of fracturability from both geological and engineering perspectives when selecting fracturing perforation positions, problems such as high fracturing construction pressure, small fracture treatment volume, and insufficient treatment occur at the selected perforation cluster positions, restricting the effective release of the productivity of tight reservoirs. To address the above problems, the use of a comprehensive evaluation technology for the fracturability of tight reservoir geological engineering to optimize the perforation position and efficiently transform fracturing wells is the key to ensuring increased reserves and production in tight reservoirs. For fracturing wells in tight reservoirs, comprehensive evaluation measures of geological engineering fracturability are taken to optimize the perforation position to create a more complex fracture network and increase the treatment volume, thereby further improving the fracturing effect.

[0039] The inventors found that in the prior art, the evaluation of the fracturability of the reservoir corresponding to the horizontal well of the fracturing well in tight reservoirs mostly uses single-factor quantitative evaluation of the brittleness index or three-parameter comprehensive quantitative evaluation from the engineering perspective in combination with in-situ stress and fracture toughness, lacking multi-factor quantitative calculation research from both reservoir geology and engineering perspectives. It is very difficult to comprehensively quantitatively calculate and characterize a large number of geological factors and engineering factors. Usually, only single-factor and three-parameter quantitative calculations in engineering are considered, and multi-source parameter dimensionality reduction calculations considering both geological and engineering factors are relatively rare.

[0040] Specifically, firstly, the comprehensive evaluation of fracability involves the dimensionality reduction and comprehensive evaluation of multi-source parameters such as geological factors and engineering factors, which is difficult to quantitatively characterize by solving mathematical equations. Secondly, the dimensions of each factor are not unified and the contribution of each factor to the quantitative evaluation of fracability is inconsistent, making it difficult to couple the multi-factor evaluation of geology and engineering. Then, the net pressure during construction has an important impact on the evaluation of engineering fracability. The greater the net pressure, the stronger the ability to break the reservoir as a whole, which is beneficial to improving the fracturing treatment effect. However, there is no precedent on how to link the net pressure with the fracability evaluation. Finally, a corresponding model has not been established for the comprehensive evaluation method of geological and engineering fracability that combines geological parameters such as total hydrocarbon content, gas content, permeability, porosity, etc. and engineering parameters such as brittleness index, fracture toughness, maximum horizontal principal stress, minimum horizontal principal stress, construction displacement, net pressure, etc. These geological and engineering factors will significantly affect the fracturing effect.

[0041] In view of the above-mentioned technical problems, an embodiment of the first aspect of the present invention provides a comprehensive evaluation method for geological and engineering fracability of tight reservoirs. In some embodiments of the present invention, as Figure 1 shown, according to the distance relationship between multiple sounding points on the fracturing section in the reservoir and the ideal point, the fracability is evaluated. The comprehensive evaluation method includes the following steps:

[0042] S101, obtain multiple evaluation indicators that can affect the fracability of the reservoir through geological and engineering aspects.

[0043] Specifically, collect continuous geological evaluation indicators and engineering evaluation indicators at different sounding depths of the horizontal wellbore in the tight reservoir. The specific evaluation indicators collected include:

[0044] Geological evaluation indicators include: the hydrocarbon generation capacity of the reservoir, such as organic matter content, kerogen content, thermal maturity, etc.; the oil / gas content of the reservoir, such as oil / gas saturation, free gas content, adsorbed gas content, etc.; the physical properties of the reservoir, such as porosity, permeability, acoustic travel time, natural gamma, formation density, and formation pressure coefficient, etc.

[0045] Engineering indicators include: brittle mineral content, brittleness index, faults, fracture pressure, Young's modulus, Poisson's ratio, horizontal in-situ stress difference coefficient, etc.

[0046] As described above, the evaluation indicators of geological sweet spots and engineering sweet spots comprehensively reflect the overall characteristics and fracability of reservoirs. Combining these indicators can more accurately evaluate the fracability of reservoirs; each indicator describes the characteristics of the reservoir from a different perspective, and considering multiple indicators together can improve the accuracy of the evaluation; some indicators may not be obvious when considered alone, but may show their importance when combined with other indicators. For example, the brittleness index and faults may have little impact on fracability when considered alone, but may show their impact on fracturing when combined; considering multiple evaluation indicators together can provide more information for engineers and increase their confidence in decision-making; by comprehensively considering various evaluation indicators, the fracturing design can be better optimized, such as determining the best fracturing intervals, selecting the most suitable fracturing fluid, and determining the best fracturing parameters, etc.; considering more evaluation indicators can help engineers more comprehensively evaluate the risks of fracturing. For example, the presence of faults may increase the risks of fracturing, and understanding this can help engineers develop better strategies to avoid or reduce these risks.

[0047] In summary, considering the above parameters can help engineers more accurately, comprehensively, and systematically evaluate the fracability of tight reservoirs, providing more information and support for fracturing design.

[0048] In any of the above embodiments, the step of obtaining multiple evaluation indicators that can affect the fracability of the reservoir specifically includes:

[0049] Obtain the evaluation indicators of continuous geological sweet spots and engineering sweet spots of the reservoir horizontal wellbore at different depths.

[0050] Construct a second model for calculating the fracability index based on the evaluation indicators of engineering sweet spots.

[0051] Use the fracability index as an evaluation indicator for evaluating fracability.

[0052] In this embodiment, first, it is necessary to collect the evaluation indicators of continuous geological sweet spots and engineering sweet spots of the reservoir horizontal wellbore at different depths. These data can be obtained through methods such as geological logging, geological sampling, and laboratory analysis; based on the collected evaluation indicators of engineering sweet spots, such as brittle mineral content, faults, fracture pressure, Young's modulus, etc., construct a second model. This model can be an empirical relationship, a mathematical equation, or a machine learning algorithm. Its purpose is to predict or calculate the fracability index of the reservoir; use the constructed second model to calculate the fracability index of the reservoir according to the input evaluation indicators of engineering sweet spots; combine the calculated fracability index with other geological sweet spot evaluation indicators to conduct a comprehensive evaluation of the fracability of the reservoir.

[0053] As can be seen from the above, by constructing a data-based model for evaluation, the scientificity and reliability of the evaluation are improved; a quantitative index (i.e., the fracability index) is provided to evaluate the fracability of the reservoir, making the evaluation more intuitive and specific; by comprehensively using the evaluation indexes of geological sweet spots and engineering sweet spots, the accuracy of the reservoir fracability evaluation is improved; a clear and intuitive index is provided to help engineers make quick decisions, such as selecting fracturing intervals and determining fracturing parameters; through a comprehensive and scientific evaluation of the reservoir, the fracturing effect can be better predicted, thereby reducing the risk of fracturing failure; through a more accurate evaluation, fracturing of reservoirs that are not suitable for fracturing can be avoided, thereby saving costs and resources.

[0054] In any of the above embodiments, the evaluation indexes considered by the second model for engineering sweet spots include brittleness index, fracture toughness, net pressure, and stress difference; and the second model includes:

[0055]

[0056] Wherein, F rac is the fracability index, B rit is the brittleness index, both a and b are weighted coefficients of effective fracture toughness, K I is the mode-I fracture toughness, K II is the mode-II fracture toughness, p net is the net pressure in the fracture, σ H is the maximum horizontal principal stress, σ h is the minimum horizontal principal stress, σ H -σ h is the stress difference.

[0057] In this embodiment, the second model is specifically an engineering sweet spot fracability index model, and compared with the Rickman, Jin, and Yuan models, improvements are made in two aspects: (1) Currently, few studies consider the influence of the minimum horizontal principal stress gradient on the fracability index, while ignoring the influence of the maximum-minimum horizontal principal stress difference on fracture diversion and the degree of formation of complex fractures; (2) Net pressure is the direct driving force for hydraulic fracture propagation, affecting the propagation trajectory, fracture length, and fracture width of hydraulic fractures, thereby affecting the fracturing treatment effect, and currently, there is no report considering the influence of net pressure on the fracability evaluation.

[0058] The fracture toughness model is:

[0059]

[0060] In the formula: K I and K II are the mode-I and mode-II fracture toughnesses of the formation, respectively, in MPa·m0.5; P c is the confining pressure, in MPa; S tis the uniaxial tensile strength of the formation, MPa.

[0061] where the confining pressure P c and the pore pressure p p are:

[0062]

[0063] In the formula: P c is the confining pressure, MPa; σ h is the minimum horizontal principal stress from well logging interpretation, MPa; δ is the effective stress coefficient, dimensionless; p p is the pore pressure, MPa; p w is the hydrostatic pressure, MPa; ρ w is the hydrostatic density, kg / m 3 ; α is the pressure coefficient, dimensionless; g is the acceleration due to gravity, m / s2; h is the vertical depth, m.

[0064] Among them, the brittleness index is characterized by the mechanical parameters of elastic modulus and Poisson's ratio. A high elastic modulus indicates that the rock property is hard and brittle, and the ability to maintain fractures after being fractured is strong. A low Poisson's ratio reflects that the rock is more likely to fracture under pressure. After normalizing the elastic modulus and Poisson's ratio, the average weighted method is used to calculate the brittleness index using the formula. The brittleness index calculation formula is:

[0065]

[0066] In the formula: E Brit —Normalized elastic modulus of the tight reservoir, E is the elastic modulus, GPa; v Brit —Normalized Poisson's ratio of the tight reservoir, v—Poisson's ratio; Emax, Emin are the highest and lowest elastic moduli of the formation in the study area; vmax, vmin are the maximum and minimum Poisson's ratios of the formation in the study area, B rit is the brittleness index, dimensionless.

[0067] Experimental results of a large number of rock mechanics parameters show that the uniaxial compressive strength of rocks is generally 8-15 times their tensile strength. Therefore, the tensile strength of rocks can be approximately calculated by the following formula (5):

[0068] S t =[0.0045·E d ·(1 - V cl ) + 0.008·E d ·V cl / K tc ;

[0069] In the formula: S t is the tensile strength of the rock, MPa; Ktc is the ratio coefficient of rock tensile and compressive strength, generally taking the value of 12.26.

[0070] Among them, the dynamic Young's modulus is:

[0071]

[0072] In the formula, E d is the dynamic Young's modulus, MPa; ρ is the density logging value, g / cm3; V s is the shear wave velocity of the rock in acoustic logging, m / s; V p is the compressional wave velocity of the rock in acoustic logging, m / s.

[0073] Based on the natural gamma logging data, the shale content of the rock at different well depths can be calculated.

[0074]

[0075] In the formula, V cl is the volume content of shale; I GR is the shale content index; GR, GR min , GR max respectively represent the natural gamma reading values of the target layer, the pure sandstone layer and the pure shale layer; GUCR is the Hilchie index, taking 3.7 for the Tertiary strata and 2 for the older strata.

[0076] The net construction pressure adopts the net pressure model in PKN as:

[0077]

[0078] In the formula: p net is the net construction pressure under the extended same fracture length L f and fracture height H f , MPa.

[0079] In any of the above embodiments, considering factors such as the hydrocarbon generation capacity of the reservoir, the oil / gas content of the reservoir, and the physical properties of the reservoir, the geological sweet spot evaluation index is preferably selected.

[0080] The geological sweet spot evaluation index mainly includes the hydrocarbon generation capacity of the reservoir: total hydrocarbon content, kerogen content, thermal maturity, etc.; the oil / gas content parameters of the reservoir: oil / gas saturation, free gas content, adsorbed gas content, etc.; the physical properties of the reservoir porosity, permeability and formation pressure coefficient, etc. Among them, the total hydrocarbon content, gas content, permeability, and porosity are particularly important for the geological sweet spot evaluation, and they can largely reflect the exploitation value and the difficulty of exploitation of the formation. In addition, other evaluation indexes can also be selected to participate in the geological sweet spot evaluation.

[0081] ① Total hydrocarbon content

[0082] The total hydrocarbon content characterizes the abundance of hydrocarbons in the reservoir. The higher the total hydrocarbon content, the higher the hydrocarbon content in the reservoir, the better the gas-bearing property geologically, and the higher the probability of gas production after fracturing. It is an important indicator for evaluating the fracturability of the reservoir. The total hydrocarbon content can be obtained from well logging results. In the relationship curve of the total hydrocarbon content against the reservoir depth, the higher the curve position, the higher the hydrocarbon content at the corresponding reservoir depth position, which is an enrichment area for oil and gas and should be the key area for fracturing transformation; the lower the curve position, the less the hydrocarbon content. When it is lower than a certain value, it can be considered that this section of the reservoir has no economic transformation value.

[0083] ② Gas content

[0084] The gas content of shale is controlled by the gas generation capacity and intensity of shale. There are internal relationships between the lost gas, desorbed gas, and residual gas and the adsorbed gas and free gas respectively. The adsorbed gas content and total gas content of shale are important parameters in the geological evaluation of shale gas content. The proportion of free gas in shale gas can not only reflect the occurrence state of natural gas in shale, but also indicate the recoverability of shale gas. The higher the gas content, the higher the probability trend of gas production.

[0085] ③ Permeability

[0086] The reservoir permeability has a direct impact on production. It is found that the greater the permeability of the transformation area, the greater the cumulative production of the reservoir. The greater the reservoir permeability, the better the fluid flow performance through the rock medium. After fracturing to form fractures, the oil and gas in the reservoir around the fractures are more likely to enter the fractures and then flow into the wellbore, resulting in higher well production and more significant stimulation effect after fracturing.

[0087] ④ Porosity

[0088] Porosity is an important parameter for evaluating the quality of the reservoir. At the same time, it is also the main basis for optimizing fracturing technology, fracture system, and construction parameters and evaluating the post-fracture effect during the formulation of fracturing construction design. The porosity in the vertical direction of the reservoir can be obtained through core analysis and well logging data, and then the relationship curve between porosity and reservoir depth can be obtained. The higher the porosity in the curve, the greater the porosity at the reservoir position corresponding to the measured depth, which is a position with better reservoir physical properties. The greater the stimulation ratio obtained by fracturing here; the lower the porosity in the curve, the smaller the porosity at the reservoir position corresponding to the measured depth, indicating that the physical properties of the corresponding reservoir here are poor, and the stimulation ratio obtained after fracturing is smaller.

[0089] In this embodiment, comprehensive analysis: These four indicators comprehensively evaluate the quality and economic value of the reservoir from different aspects. The total hydrocarbon content and gas content evaluate from the perspective of the richness of oil and gas resources, while the permeability and porosity evaluate from the aspects of fluid mobility and storage capacity; these four indicators can all be quantitatively measured, so specific numerical values can be provided, which helps to conduct quantitative comparison and analysis; based on the evaluation of these indicators, clear guidance can be provided for the development strategy of the oil and gas field, such as determining the fracturing sections, selecting appropriate fracturing fluids and additives, etc.; through the evaluation of these key indicators, high-quality reservoirs can be identified, so as to develop them targeted and reduce the development risks caused by selecting low-quality reservoirs; selecting reservoirs with high total hydrocarbon content, high gas content, high permeability and high porosity for development can obtain higher oil and gas production, thus improving economic benefits; through the comprehensive evaluation of these indicators, reservoirs with higher economic value can be preferentially developed, so as to optimize the resource allocation and achieve the maximum utilization of resources; during the development process, these indicators can also be used as the basis for monitoring and management, such as monitoring the production status of the reservoir and evaluating the fracturing effect, etc.

[0090] In summary, selecting the total hydrocarbon content, gas content, permeability, and porosity as the main indicators for geological sweet spot evaluation can not only comprehensively and accurately evaluate the quality and economic value of the reservoir, but also help to improve the development efficiency of the oil and gas field and reduce the development risks.

[0091] S102. Construct an evaluation matrix considering the data of all sounding points on the fracturing section according to the influence degree of each evaluation index on the fracability.

[0092] Specifically, select the geological sweet spot evaluation index and the engineering sweet spot evaluation index to construct the evaluation matrix

[0093] First, select the evaluation indexes of the evaluation area: the geological sweet spot evaluation index and the engineering sweet spot evaluation index.

[0094] The geological sweet spot evaluation indexes mainly include: the hydrocarbon generation capacity of the reservoir, such as organic matter content, kerogen content, thermal maturity, etc.; the oil / gas content of the reservoir, such as oil / gas saturation, free gas content, adsorbed gas content, etc.; the physical properties of the reservoir, such as porosity, permeability and formation pressure coefficient, etc.

[0095] The engineering sweet spot indexes mainly include: brittle mineral content, brittleness index, faults, fracture pressure, Young's modulus, Poisson's ratio, horizontal stress difference, fracture toughness, construction net pressure, etc.

[0096] Thus, an evaluation matrix composed of n evaluation indexes within a certain fracturing section can be obtained:

[0097] X=(x ij ) mn, where \(i = 1, 2, \ldots, m\); \(j = 1, 2, \ldots, n\);

[0098] In the formula: \(X\) is an evaluation matrix composed of \(n\) evaluation indicators and \(m\) detection points in the selected evaluation area; \(x_{ij}\) is the value corresponding to the \(i\)-th detection point of the \(j\)-th evaluation indicator.

[0099] Step Five: Use the range transformation of "the larger the better" and "the larger the worse" to standardize the original data

[0100] There are great differences in the dimensions, effective ranges, and orders of magnitude of different geological / engineering indicators. In order to make the data more comparable, the range transformation is used to standardize the original data. The evaluation indicators are divided into positive indicators and negative indicators. A positive indicator indicates that the larger the indicator value, the better, while a negative indicator represents that the larger the indicator value, the worse.

[0101] For positive ideal indicators, such as the fracturability index, total hydrocarbon content, porosity, permeability, etc., use the range transformation of "the larger the better" for standardization:

[0102]

[0103] For negative ideal indicators, such as the fracture pressure, horizontal in-situ stress difference coefficient, etc., use the range transformation of "the larger the worse" for standardization:

[0104]

[0105] In the formula: —The value corresponding to the \(i\)-th detection point of the \(j\)-th evaluation parameter after standardization; —The maximum value of all detection points of the fracturing stage corresponding to the \(j\)-th evaluation indicator in the evaluation matrix; —The minimum value of all detection points of the fracturing stage corresponding to the \(j\)-th evaluation indicator in the evaluation matrix.

[0106] To obtain the standardized evaluation matrix \(X\) * :

[0107]

[0108] In the formula: —The value corresponding to the \(i\)-th detection point of the \(j\)-th evaluation indicator after standardization.

[0109] S103. Obtain the influence relationship of each evaluation indicator on the fracturability, and modify the evaluation matrix according to the influence relationship.

[0110] Specifically, the steps to modify the evaluation matrix according to the influence relationship specifically include:

[0111] Obtain the first correlation relationship between the evaluation index and the fracability in terms of numerical increase and decrease. According to the extreme value of the evaluation index and the first correlation relationship, correct each sounding point in the current evaluation index in the evaluation matrix.

[0112] Obtain the second correlation relationship between the evaluation index and its optimal parameter in terms of distance, and use the second correlation relationship as the weight to correct the evaluation index corresponding to the second correlation relationship in the evaluation matrix.

[0113] Here, based on experimental data or actual production data, analyze the correlation relationship between the evaluation index and the fracability. For example, through methods such as scatter plots, correlation analysis, or regression analysis, determine the relationship between each evaluation index and the fracability. Once this relationship is determined, for example, if it is found that when a certain index increases, the fracability also increases, then it can be considered that there is a positive correlation first correlation relationship between them; according to the extreme value of the evaluation index, determine the position of this index in the evaluation matrix. Then, according to the first correlation relationship, correct this index in the evaluation matrix. For example, if it is found that an index has a positive correlation first correlation relationship with the fracability, then in the evaluation matrix, the extreme value of this index should match the extreme value of the fracability; the distance relationship between the evaluation index and its optimal parameter needs to be determined based on actual data. This can be achieved by comparing the best fracturing effect in actual production with the value of the evaluation index. Once this relationship is determined, for example, if it is found that the closer an index is to its optimal value, the better the fracturing effect, then it can be considered that there is a second correlation relationship between this index and its optimal parameter; according to the second correlation relationship, use this relationship as the weight to correct the evaluation index related to it in the evaluation matrix. In this way, each index in the evaluation matrix will be weighted and corrected according to its correlation degree with the fracability.

[0114] As can be seen from the above, to improve the accuracy of the evaluation: By correcting the evaluation matrix according to actual data, it can be ensured that the evaluation matrix is closer to the actual situation, thereby improving the accuracy of the evaluation; It not only considers the absolute value of the index, but also considers the distance between the index and its optimal value, thus more comprehensively evaluating the impact of each index on the fracability; The accurate and comprehensive evaluation matrix provides an important basis for decision-makers, helping them formulate more reasonable and effective fracturing strategies; Accurate evaluation can help decision-makers avoid unnecessary attempts and mistakes, thus saving resources and costs; Accurate and comprehensive evaluation helps to improve the fracturing effect, thereby increasing oil and gas production and improving economic benefits.

[0115] In summary, the method of correcting the evaluation matrix according to the influence relationship can not only improve the accuracy of the evaluation, but also provide strong decision-making support for decision-makers, thereby improving the fracturing effect and economic benefits.

[0116] In any of the above embodiments, the step of correcting the data of each sounding point in the current evaluation index in the evaluation matrix specifically includes:

[0117] According to the first correlation relationship, if the index value of the evaluation index is positively correlated with the fracability, the current evaluation index is a positive ideal index; if the index value of the evaluation index is negatively correlated with the fracability, the current evaluation index is a negative ideal index.

[0118] The positive ideal index is corrected based on the following formula:

[0119] (1 ≤ i ≤ m, j is the corresponding positive ideal index parameter column);

[0120] The negative ideal index is corrected based on the following formula:

[0121] (1 ≤ i ≤ m, j is the corresponding negative ideal index parameter column);

[0122] Replace the corresponding evaluation index in the evaluation matrix with the corrected positive ideal index and negative ideal index.

[0123] Wherein, is the value corresponding to the i-th sounding point of the j-th evaluation index after correction, is the maximum value of all sounding points of the fracturing section corresponding to the j-th evaluation index in the evaluation matrix, is the minimum value of all sounding points of the fracturing section corresponding to the j-th evaluation index in the evaluation matrix, k is the number of sounding points, m is the last sounding point, and x ij is the value corresponding to the i-th sounding point of the j-th evaluation index before correction.

[0124] In this embodiment, through the above formula, the data in the original evaluation matrix is standardized. The standardized data is convenient for analysis and comparison, ensuring that meaningful comparisons can be made between evaluation indexes with different measurement ranges and units; according to the relationship between the evaluation index and the fracability, the positive ideal index and the negative ideal index are distinguished, which helps to identify which indexes are positively correlated with the research target and which are negatively correlated. This classification provides clear guidance on the importance of each index; by considering the specific correlation relationship between the evaluation index and the fracability for correction, the evaluation can be made more accurate, thus providing a more reasonable evaluation result for decision-makers; in the corrected evaluation matrix, high values represent closer to the positive ideal state, and low values represent closer to the negative ideal state. In this way, decision-makers can more easily identify the key indexes affecting the fracability.

[0125] In summary, according to the above correction method, the fracability of each sounding point can be evaluated more accurately and comprehensively, providing a more scientific and reasonable evaluation basis for decision-makers, thus helping to optimize the fracturing strategy, increase oil and gas production, and improve economic benefits.

[0126] Specifically, a target planning optimization evaluation model is established based on the numerical information of the evaluation matrix, and a Lagrangian function is constructed to solve the weights; considering the positive and negative ideal evaluation indicators and the contribution of attributes to the distance, the entropy weight method is used to calculate the weights of the price index attribute values, and the weighted normalized evaluation matrix is ​​calculated.

[0127] In the process of evaluating indicators, the weight of the attribute value of the evaluation indicator has a great influence on the final score of the evaluated object. Therefore, a target planning optimization evaluation model is established based on the numerical information of the evaluation matrix, and the weight of the attribute value of the evaluation indicator is calculated by mathematical methods. Suppose the weights corresponding to the n evaluation indicators are w1, w2, ..., w n , then the sum of the weighted distances between the detection point in the fracturing section and the positive ideal index and the negative ideal index is:

[0128]

[0129] In the sense of distance, f i The smaller (w) is, the better. Based on this, the following multi-objective planning model is established.

[0130] minf(w)=(f1(w),f2(w),.....f m (w));

[0131] in,

[0132] The weight is solved by constructing Lagrangian function:

[0133]

[0134] in,

[0135] Considering the contribution of positive and negative ideal evaluation indicators to the distance, the entropy weight method is used to calculate the attribute weights of positive and negative ideal indicators. for:

[0136]

[0137] in, j is a positive ideal index parameter column; j is the negative ideal index parameter column.

[0138] Combine the contributions of the positive ideal and negative ideal evaluation index attributes to the distance and perform a weighted average:

[0139]

[0140] Using the obtained weight coefficients, the weighted normalized evaluation matrix X can be obtained # :

[0141]

[0142] In the formula: is the value corresponding to the i-th detection point of the j-th evaluation index after weighted normalization processing.

[0143] In any of the above embodiments, the step of using the second correlation relationship to correct the evaluation index corresponding to the second correlation relationship in the evaluation matrix specifically includes:

[0144] Construct a multi-objective programming model considering the weights of each evaluation index;

[0145] According to the second correlation relationship and the multi-objective programming model, calculate the attribute weights of the positive ideal index and the negative ideal index respectively;

[0146] Perform weighted average processing on the attribute weights, and correct the evaluation matrix through the processed attribute weights.

[0147] In this embodiment, by constructing a multi-objective programming model and calculating the attribute weights in combination with the second correlation relationship, the objective weighting of the evaluation index is realized, and the influence of subjective factors on the evaluation result is reduced; the weight calculation based on the second correlation relationship and the multi-objective programming model can dynamically adjust the weights of the evaluation indexes according to different scenarios and conditions, making the evaluation more accurate and targeted; the weighted average processed attribute weights ensure that each evaluation index is considered according to its importance, so that the evaluation result is more comprehensive and comprehensive; the corrected evaluation matrix combines the weight considerations of various factors, provides a more clear and specific basis for decision-makers, and helps to make more accurate decisions; the weighting method of the multi-objective programming model allows adjusting the weights in different evaluation scenarios, making the evaluation method have better flexibility and adaptability; through the calculation of the attribute weights, decision-makers can clearly see the relative importance of each evaluation index in the overall evaluation, which helps to more clearly perform priority ranking.

[0148] In summary, the method of using the second correlation relationship to correct the evaluation matrix not only enhances the objectivity, comprehensiveness and comprehensiveness of the evaluation, but also improves the adaptability and flexibility of the evaluation, and provides a more scientific, clear and reliable decision-making basis.

[0149] S104. Obtain the distance relationship between each sounding point on the fracturing section and the ideal point according to the corrected evaluation matrix, so as to construct a first model for evaluating the fracturability.

[0150] In any of the above embodiments, the step of obtaining the distance relationship between each sounding point on the fracturing section and the ideal point according to the corrected evaluation matrix specifically includes:

[0151] Obtain the ideal value sequence of the ideal point through the corrected evaluation matrix.

[0152] Calculate the Euclidean distance between all evaluation indexes of each sounding point in the fracturing section and the ideal value sequence.

[0153] The first model is specifically the following formula:

[0154]

[0155] Where is the Euclidean distance between the sounding position x oi in the fracturing section and the positive ideal value, and the pressure the Euclidean distance between the sounding position x oi in the fracturing section and the negative ideal value, and d i (x oi ) is the Euclidean distance between the sounding position x oi in the fracturing section and the ideal value, and x oi is the sounding corresponding to the i-th sounding point in the fracturing section, is in the evaluation matrix the corresponding value after correction.

[0156] In this embodiment, by calculating the Euclidean distance between each sounding point and the ideal value sequence, the characteristics and differences of each sounding point can be described more precisely, so as to provide more detailed information for reference; using the Euclidean distance as the evaluation criterion reduces the interference of subjective evaluation and ensures the objectivity of the evaluation result; comprehensively considering the distances of the positive ideal value and the negative ideal value can comprehensively evaluate the performance of the sounding point; the distance relationship provides an intuitive way to evaluate the performance of each sounding point, which is convenient for understanding and interpretation; by calculating the distance relationship between each sounding point and the ideal point, the decision maker can quickly determine which sounding points are close to the ideal state and which need to be improved; regardless of how the evaluation matrix is corrected, as long as the ideal value sequence is obtained, this model can be applied, showing good adaptability; since each sounding point is compared with the same ideal value sequence, the differences between different sounding points can be seen more clearly.

[0157] Specifically, based on the multi-source parameter dimensionality reduction to approximate the ideal solution and the Euclidean distance theory method, considering the influence of many parameters in geological engineering comprehensively, a comprehensive evaluation model for the fracturability of geological engineering is established

[0158] The direct impact on the development effect of shale reservoirs is mainly reflected in the difficulty of reservoir fracturing transformation, the effective volume fracturing scale, and the selection of horizontal well fracturing positions. The selection of geological engineering sweet spots in shale reservoirs is restricted by the heterogeneity of rock mechanics parameters, permeability, porosity, gas content, brittleness, and fracturability widely existing in the reservoirs, which will lead to differences in the geological sweet spot evaluation and engineering parameter sweet spot evaluation of different well sections. In addition, there are many evaluation parameters, and how to select sweet spots directly determines the quality of fracturing effects. Considering that the comprehensive sweet spot area of the reservoir should be affected by both geological and engineering factors, the compressibility can be redefined as a comprehensive evaluation index of reservoir geological conditions and fracturing construction effects, that is, it characterizes the ability of unconventional reservoirs to obtain oil and gas production through fracturing transformation. Therefore, based on the compressibility evaluation method of comprehensive sweet spot analysis, the compressibility index of the reservoir is constructed using geological and engineering parameters, which is used as the key index to quantify the comprehensive sweetness of the reservoir, and quantitatively characterizes the fracturable quality of the reservoir.

[0159] There are many factors and complex relationships affecting the selection of points. Each factor may play different roles in the selection of fracturing points at different levels. Therefore, in order to comprehensively consider the influence of various factors on the selection of fracturing points, the multi-source parameter dimensionality reduction approximation ideal solution method is used to quickly select the perforation positions of horizontal wells. For the evaluation matrix after weighted normalization processing, the ideal value sequence is selected to calculate the Euclidean distance, that is, calculate the distance between all evaluation index values of the i-th point in the fracturing section and the ideal value sequence of the evaluation index column.

[0160] Select the optimal parameters of geological evaluation indicators and engineering evaluation indicators to construct the ideal parameter vector. Based on the Euclidean distance theory, calculate the positive and negative ideal Euclidean distances (indicating the degree of closeness to the best / worst values of the positive ideal indicators).

[0161] A comprehensive evaluation method for the geological engineering fracturability of tight reservoirs provided by the present invention, aiming at the difficulties and deficiencies in the current comprehensive evaluation of fracturability, the inventor has conducted a comprehensive study on the characteristics of multiple geological and engineering factors of tight reservoirs on the basis of fully investigating the research status of geological sweet spot indicators, engineering sweet spot indicators, and engineering fracturability models of tight reservoirs at home and abroad. A complete comprehensive evaluation model for the geological engineering fracturability of tight reservoirs is established to analyze the geological engineering fracturability evaluation problems of comprehensive geological parameters such as total hydrocarbon content, gas content, permeability, and porosity, and engineering parameters such as brittleness index, fracture toughness, maximum horizontal principal stress, minimum horizontal principal stress, construction displacement, and net pressure. This model comprehensively considers the influence of geological parameters and engineering parameters on the fracturability of the reservoir, and can accurately and quantitatively evaluate the fracturability of tight reservoirs.

[0162] Another embodiment of the first aspect of the present invention proposes a specific implementation method for the comprehensive evaluation method of the geological engineering fracturability of tight reservoirs. The specific implementation method includes the following steps:

[0163] Step 1. Collect continuous geological sweet spot evaluation indicators and engineering sweet spot evaluation indicators at different depths of the horizontal wellbore in the tight reservoir.

[0164] Step 2. Consider factors such as brittleness index, fracture toughness, net pressure, and stress difference, and establish an engineering sweet spot fracability index model.

[0165] Step 3. Consider factors such as reservoir hydrocarbon generation capacity, reservoir oil / gas content, and reservoir physical properties, and optimize the geological sweet spot evaluation indicators.

[0166] Step 4. Select geological sweet spot evaluation indicators and engineering sweet spot evaluation indicators to construct an evaluation matrix.

[0167] Step 5. Use the range transformation of the better the larger and the worse the larger to standardize the original data.

[0168] Step 6. Establish a goal programming optimization evaluation model based on the numerical information of the evaluation matrix, construct a Lagrangian function to solve the weights; consider the positive and negative ideal evaluation indicators and the contribution of attributes to the distance, calculate the weights of the evaluation index attribute values by the entropy weight method, and calculate the weighted normalized evaluation matrix.

[0169] Step 7. Based on the multi-source parameter dimensionality reduction approximation to the ideal solution and the Euclidean distance theory method, comprehensively consider the influence of many geological engineering parameters, and establish a comprehensive evaluation model for geological engineering fracability.

[0170] Step 8. Compare and verify with other models, and optimize the perforation position.

[0171] Among them, the collection of evaluation indicators in Step 1 specifically includes that the geological sweet spot evaluation indicators include: the hydrocarbon generation capacity of the reservoir, such as organic matter content, kerogen content, thermal maturity, etc.; the reservoir oil / gas content, such as oil / gas saturation, free gas content, adsorbed gas content, etc.; the reservoir physical properties, such as porosity, permeability, acoustic travel time, natural gamma, formation density, and formation pressure coefficient, etc.; the engineering sweet spot indicators include: brittle mineral content, brittleness index, fault, fracture pressure, Young's modulus, Poisson's ratio, horizontal in-situ stress difference coefficient, etc.

[0172] Another specific implementation method of the comprehensive evaluation method for the fracturability of tight reservoirs proposed in another embodiment of the first aspect of the present invention obtains the geological and engineering sweet spot evaluation indicators at each sounding depth of the horizontal wellbore in the tight reservoir through various geological, geophysical, and geochemical means. This may involve data such as geological cores, well logging, seismic, and mapping; use relevant geological and engineering data (such as brittleness index, fracture toughness, etc.) to construct a mathematical model that can evaluate the engineering fracturability of the reservoir; based on factors such as the hydrocarbon generation capacity, oil / gas content, and physical properties of the reservoir, screen out the most important geological sweet spot evaluation indicators; integrate the evaluation indicators of geological sweet spots and engineering sweet spots in an evaluation matrix, and each indicator has a numerical value; in order to eliminate the dimensional influence between evaluation indicators, use the range transformation to standardize the data; use methods such as goal programming, Lagrangian function, and entropy weight method to determine the weight of each evaluation indicator; based on the multi-parameter dimensionality reduction approximation ideal solution and Euclidean distance theory method, construct a comprehensive evaluation model that can integrate the influence of geological and engineering attributes; compare with other existing models to verify the effectiveness of the new model, and then use this model to optimize the perforation location to ensure that the perforation is located in the area with the best fracturability.

[0173] As can be seen above, integrating geological and engineering data provides a more comprehensive evaluation method; by using methods such as goal programming and entropy weight method, the weight of each evaluation indicator can be determined more accurately; data standardization ensures that all indicators are compared with a unified standard in the model; effective perforation locations can improve production efficiency, reduce the possibility of ineffective fracturing, and maximize resource recovery; by accurately selecting perforation locations, the number of perforations and the cost of fracturing can be reduced, while increasing the oil and gas production; in-depth understanding and evaluation of the reservoir can greatly reduce development risks and improve the success rate of the project.

[0174] Another embodiment of the first aspect of the present invention proposes a method for optimizing perforation locations based on a comprehensive evaluation method for the fracturability of tight reservoir geological engineering, such as Figures 2-7 , and the method for optimizing perforation locations includes the following steps:

[0175] ① Comparison of fracturability index evaluation models:

[0176] Based on the logging data of 11,755 sounding points in the horizontal section of Well X, the fracability index, brittleness index, gas content, TOC content, porosity, and permeability are selected as positive ideal evaluation indicators, and the stress difference is selected as the negative ideal evaluation indicator. Using the established comprehensive geological and engineering fracability point selection method, geological and engineering sweet spot evaluation is carried out. Based on the established fracability index model, it is compared and verified with theoretical models such as Rickman, Jin, and Yuan, as shown in Table 1. The Rickman model only considers the brittleness index; the Jin model considers the average weighted of the brittleness index and the fracture toughness of Type I; the Yuan Junliang model considers the brittleness index, fracture toughness of Type I and Type II; the Yuan model considers the average weighted of the brittleness index, fracture toughness of Type I and Type II, and the minimum horizontal principal stress gradient; while the model of this patent considers the influence of net pressure, brittleness index, fracture toughness of crack propagation, and stress difference, as shown in Table 1.

[0177] Table 1 Model verification table

[0178]

[0179] Taking the 10th fracturing section (3546 - 3616m) of Well X as an example, the established engineering sweet spot fracability evaluation model is compared and verified with the existing models and the actual gas production measured by fiber optic logging. As Figure 2 shown.

[0180] Figure 2 From left to right, the fracability index curves are the Rickman model, Jin model, Yuan model, and the model of this patent, and are compared with the actual gas production profile measured by fiber optic logging of this well. From Figure 2 it can be seen that the model of this patent has a high overall consistency with the existing models, and the high values of the obtained fracability index correspond to high gas production, verifying the correctness of the model of this patent; secondly, there are typical differences between the model of this patent and the existing models. For example, Figure 2 the Rickman model and Jin model of the first perforation cluster (3558 - 3558.5m) are low values, while the model of this patent considers the influence of net pressure and stress difference and is a high value of the fracability index, which is consistent with the high gas production evaluation. Since the wellbore azimuth of Well X is perpendicular to the direction of the maximum principal stress, transverse fractures are formed without turning, which is consistent with the result of the Yuan model considering the minimum horizontal principal stress gradient and the evaluation of the model of this patent considering the stress difference, fully demonstrating the correctness of the model of this patent. To sum up, the fracability evaluation considering engineering sweet spot and geological sweet spot factors has a high degree of consistency with the actual gas production, and can better take into account the geological engineering integration sweet spot evaluation of geological aspects such as oil and gas content and physical properties, and engineering aspects such as fracability.

[0181] ② Comparison of comprehensive geological and engineering fracability evaluation models:

[0182] Select gas content, TOC content, permeability, and porosity as geological sweet spot evaluation parameters and compare them with the actual gas production to select sweet spots from a geological perspective.

[0183] It can be seen from Figure 3 that only selecting perforation based on geological sweet spots may lead to contradictions where the geological evaluation is poor while the actual production is good. For example, at the depth marked as the 4th perforation cluster at 3579 - 3579.5m, the gas content is low, the TOC content is high, the permeability is high, and the porosity is high; for the 2nd perforation cluster at 3599.5 - 3600m, the gas content is high, the TOC content is low, the permeability is low, and the porosity is low. Therefore, only selecting perforation based on geological sweet spots can only meet the congenital conditions that areas with rich oil and gas resources and good physical properties have development potential, but cannot guarantee the formation of a complex fracture network during fracturing construction.

[0184] Select the fracability index, brittleness index, and stress difference as engineering sweet spot evaluation parameters and compare them with the actual gas production to select sweet spots from an engineering perspective.

[0185] It can be seen from Figure 4 that only selecting perforation based on engineering sweet spots may lead to contradictions where the engineering evaluation is poor while the actual production is good. For example, at the depth of the 3rd perforation cluster at 3579 - 3579.5m, the fracability index is low, the brittleness index is high, and the stress difference is low. Therefore, only selecting perforation based on engineering sweet spots can only meet the formation of a complex fracture network during fracturing construction, but cannot guarantee rich oil and gas resources and good physical properties.

[0186] Select gas content, TOC content, permeability, and porosity as geological sweet spot evaluation parameters, select the fracability index, brittleness index, and stress difference as engineering sweet spot evaluation parameters and compare them with the actual gas production to select sweet spots from an integrated geological and engineering perspective. Use the established comprehensive evaluation model of geological engineering fracability for comparison and verification.

[0187] It can be seen from Figure 5 that only selecting perforation based on engineering sweet spots may lead to contradictions where the engineering evaluation is poor while the actual production is good; it may also lead to contradictions where the geological evaluation is good while the actual production is poor. And the curve selected from the comprehensive evaluation of geological engineering fracability is basically consistent with the production curve. Therefore, only by conducting a comprehensive evaluation of geological engineering fracability can the expected fracturing effect be achieved.

[0188] ③ Optimization of perforation location:

[0189] The optimization of perforation positions mainly refers to the engineering sweet spot indicators of Well Y (including brittleness index, Poisson's ratio, horizontal principal stress difference coefficient, Young's modulus, minimum horizontal principal stress, etc.) and geological sweet spot indicators (including permeability, porosity, GR, etc.), and comprehensively selects perforation positions by using the established multi-source parameter dimensionality reduction approximation ideal solution method.

[0190] Figure 6 Taking the 7th fracturing stage at 2770 - 2860m as an example, through engineering sweet spot indicators, geological sweet spot indicators, comprehensive indicators, and fracture pressure curves, using the established multi-source parameter dimensionality reduction approximation ideal solution method, 6 clusters of perforation positions are comprehensively optimized as 2774m, 2788m, 2803m, 2818m, 2834m, 2850m according to the principle of similarity and proximity, where the cluster spacing is 14m, 15m, 15m, 16m, 16m.

[0191] Figure 7 Taking the 9th fracturing stage at 2583 - 2681m as an example, through engineering sweet spot indicators, geological sweet spot indicators, comprehensive indicators, and fracture pressure curves, using the established multi-source parameter dimensionality reduction approximation ideal solution method, 6 clusters of perforation positions are comprehensively optimized as 2598.2m, 2613.9m, 2627.4m, 2642.3m, 2653.5m, 2668m according to the principle of similarity and proximity, where the cluster spacing is 15.7m, 13.5m, 14.9m, 11.2m, 14.5m.

[0192] Another embodiment of the first aspect of the present invention proposes a perforation position optimization method based on a comprehensive evaluation method for the fracturability of tight reservoir geological engineering. The original data of geological sweet spot indicators and engineering sweet spot indicators, such as brittleness index, Poisson's ratio, minimum horizontal principal stress, permeability, porosity, GR, etc., are collected within a specific well section. In order to eliminate the influence of the dimension and order of magnitude of each evaluation index, the original data is standardized so that each evaluation index can be compared on the same scale. Based on the established multi-source parameter dimensionality reduction approximation ideal solution method, the geological sweet spot indicators and engineering sweet spot indicators are comprehensively evaluated to obtain a comprehensive index. The comprehensive index is compared with the actual gas production of the well to verify the correctness and practicability of the model. According to the comprehensive index and the fracture pressure curve, the optimal perforation position is determined. Considering the cluster spacing and various geological and engineering factors, specific perforation layout is carried out. The prediction results of the model are compared with other existing models or theories, and at the same time compared with the actual production data to verify the reliability and superiority of the model.

[0193] As can be seen from the above, by comprehensively considering geological sweet spots and engineering sweet spots, the evaluation is more comprehensive, capable of taking into account both the geological characteristics of the oil and gas reservoir and the engineering characteristics of the fracturing operation; through the comprehensive evaluation of multi-source parameters, the perforation position can be selected more precisely to ensure the fracturing effect and gas production; this model can be applied to different geological backgrounds and engineering conditions, with strong adaptability and universality; accurate selection of the perforation position can improve the fracturing effect, increase gas production, and thus improve economic efficiency; through this model, perforation in areas with poor geological conditions or unsuitable engineering conditions can be avoided, thereby reducing construction risks and avoiding waste of resources.

[0194] In summary, the method for optimizing the perforation position by comprehensively considering geological and engineering factors can not only increase the production of oil and gas wells, but also improve construction efficiency, reduce risks, and bring greater economic benefits to oil and gas development.

[0195] An embodiment of the second aspect of the present invention provides a comprehensive evaluation device. In some embodiments of the present invention, the comprehensive evaluation device 2 is used to implement the comprehensive comparison method in any of the above technical solutions, such as Figure 8 shown, the comprehensive evaluation device 2 includes:

[0196] A data collection module 201, configured to obtain and store data of all evaluation indicators that can affect the fracturability of the reservoir;

[0197] An evaluation index screening module 202, configured to screen the evaluation indicators in terms of geology and engineering according to the influence degree of each evaluation indicator on the fracturability.

[0198] An evaluation matrix construction module 203, configured to construct an evaluation matrix considering all sounding points on the fracturing section.

[0199] An evaluation matrix correction module 204, configured to correct the evaluation matrix according to the relationship between each evaluation indicator and the fracturability.

[0200] A comprehensive evaluation model construction module 205, configured to calculate the distance between each sounding point and the ideal point according to the corrected evaluation matrix and the data of the evaluation indicators, and construct a comprehensive evaluation model for evaluating the fracturability.

[0201] A visualization and reporting module 206, configured to generate a visualized evaluation result according to the comprehensive evaluation model and generate an evaluation report.

[0202] A comprehensive evaluation device provided by the present invention collects data of multiple evaluation indicators that may affect fracability, evaluates the influence degree of each evaluation indicator on fracability through expert review or statistical methods, screens the evaluation indicators in terms of geology and engineering, and selects the most relevant indicators; according to the selected evaluation indicators, form an evaluation vector for each sounding point on the fracture section, and combine the evaluation vectors of all sounding points into an evaluation matrix; analyze the relationship between each evaluation indicator and fracability; correct the evaluation matrix according to the relationship weight; adopt a suitable algorithm or model, such as Euclidean distance or other similarity measurement methods, to calculate the distance between each sounding point and the ideal point; combine these distance data to construct a comprehensive evaluation model; according to the comprehensive evaluation model, generate a visual chart or map to display the fracability score or level of each sounding point; generate a detailed report containing all evaluation data, analysis results and suggestions.

[0203] As can be seen from the above, through screening, it is ensured that the evaluation process is more accurate and efficient, and unnecessary or redundant data is excluded, making the evaluation more professional; a systematic and unified format evaluation matrix is constructed to provide structured data for subsequent evaluation; a quantitative and systematic method is provided to evaluate the fracability of each sounding point, so as to provide specific and clear suggestions for decision-makers; the evaluation results are presented through an intuitive visualization method, enabling non-technical personnel to understand; and the detailed report provides in-depth information and basis for experts and decision-makers.

[0204] In summary, this comprehensive evaluation system provides a complete, systematic and efficient tool for the oil and gas industry, helping decision-makers evaluate the fracability of reservoirs more scientifically and accurately and formulate corresponding development strategies.

[0205] An embodiment of the third aspect of the present invention proposes an electronic device. In some embodiments of the present invention, as Figure 9 shown, an electronic device is provided. The electronic device may include desktop computers, notebooks, palmtop computers, cloud servers and other electronic devices. The electronic device 3 may include but is not limited to a processor 301 and a memory 302. Those skilled in the art can understand that Figure 9 this is only an example of the electronic device 3 and does not constitute a limitation on the electronic device 3. It may include more or fewer components than shown in the figure, or different components.

[0206] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0207] The memory 302 may be an internal storage unit of the electronic device 3. For example, the hard disk or memory of the electronic device 3. The memory 302 may also be an external storage device of the electronic device 3. For example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 3. The memory 302 may also include both an internal storage unit and an external storage device of the electronic device 3. The memory 302 is used to store computer programs and other programs and data required by the electronic device.

[0208] Embodiments of the fourth aspect of the present invention propose a computer-readable storage medium. In some embodiments of the present invention, a computer-readable storage medium is provided. When the computer-readable storage medium is executed by the processor 301, the steps of the above method are implemented. Therefore, the computer-readable storage medium provided by the fourth aspect of the present invention has all the technical effects of the above steps, which will not be elaborated here.

[0209] Those skilled in the art can clearly understand that for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In practical applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiments, which will not be elaborated here.

[0210] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this disclosure.

[0211] In the embodiments provided in this disclosure, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. Multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0212] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes of the above-described method embodiments of this disclosure, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above-described method embodiments. The computer program can include computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0213] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the present disclosure's various embodiments, and should all be included within the protection scope of the present disclosure.

Claims

1. A comprehensive evaluation method for the fracturability of geological engineering in tight reservoirs, characterized in that, Evaluate the fracability according to the distance relationship between multiple sounding points on the fracturing section in the reservoir and the ideal point. The comprehensive evaluation includes the following steps: Obtain multiple evaluation indicators that can affect the fracability of the reservoir through geological and engineering aspects; Construct an evaluation matrix considering the data of all the sounding points on the fracturing section according to the influence degree of each evaluation indicator on the fracability; Obtain the influence relationship of each evaluation indicator on the fracability, and correct the evaluation matrix according to the influence relationship; Obtain the distance relationship between each sounding point on the fracturing section and the ideal point according to the corrected evaluation matrix, so as to construct a first model for evaluating the fracability.

2. The comprehensive evaluation method according to claim 1, characterized in that The step of obtaining multiple evaluation indicators that can affect the fracability of the reservoir specifically includes: Obtain the evaluation indicators of continuous geological sweet spots and engineering sweet spots of the horizontal wellbore of the reservoir at different sounding depths; Construct a second model for calculating the fracability index according to the evaluation indicators of the engineering sweet spots; Use the fracability index as one of the evaluation indicators for evaluating the fracability.

3. The comprehensive evaluation method according to claim 2, wherein The evaluation indicators of the engineering sweet spots considered by the second model include brittleness index, fracture toughness, net pressure and stress difference; And the second model includes: wherein, the F rac is the fracability index, the B rit is the brittleness index, both a and b are the weighted coefficients of effective fracture toughness, the K I is the mode I fracture toughness, the K II is the mode II fracture toughness, the p net is the net pressure in the fracture, the σ H is the maximum horizontal principal stress, the σ h is the minimum horizontal principal stress, the σ H -σ h is the stress difference.

4. The comprehensive evaluation method according to claim 1, wherein The step of correcting the evaluation matrix according to the influence relationship specifically includes: Obtain the first correlation relationship between the evaluation indicator and the fracability in terms of numerical increase and decrease. According to the extreme value of the evaluation indicator and the first correlation relationship, correct each sounding point in the current evaluation indicator in the evaluation matrix; Obtain the second correlation relationship between the evaluation indicator and its optimal parameter in terms of distance, and use the second correlation relationship as a weight to correct the evaluation indicator corresponding to the second correlation relationship in the evaluation matrix.

5. The comprehensive evaluation method according to claim 4, wherein The step of correcting the data of each sounding point in the current evaluation indicator in the evaluation matrix specifically includes: According to the first correlation relationship, if the index value of the evaluation indicator is positively correlated with the fracability, the current evaluation indicator is a positive ideal indicator; if the index value of the evaluation indicator is negatively correlated with the fracability, the current evaluation indicator is a negative ideal indicator; The positive ideal indicator is corrected based on the following formula: The negative ideal indicator is corrected based on the following formula: Replace the corresponding evaluation indicator in the evaluation matrix with the corrected positive ideal indicator and negative ideal indicator; Among them, the is the value corresponding to the i-th sounding point of the j-th evaluation index after correction, j is the index sequence, is the maximum value of all sounding points of the fracturing stage corresponding to the j-th evaluation index in the evaluation matrix, is the minimum value of all sounding points of the fracturing stage corresponding to the j-th evaluation index in the evaluation matrix, where k is the number of sounding points, m is the last sounding point, and x ij is the value corresponding to the i-th sounding point of the j-th evaluation index before correction.

6. The comprehensive evaluation method according to claim 5, wherein, The step of using the second correlation relationship as a weight to correct the evaluation indicator corresponding to the second correlation relationship in the evaluation matrix specifically includes: Construct a multi-objective programming model considering the weight of each evaluation indicator; Calculate the attribute weights of the positive ideal indicator and the negative ideal indicator respectively according to the second correlation relationship and the multi-objective programming model; Perform weighted average processing on the attribute weights, and correct the evaluation matrix through the processed attribute weights.

7. The comprehensive evaluation method according to claim 6, wherein The step of obtaining the distance relationship between each sounding point on the fracturing section and the ideal point according to the corrected evaluation matrix specifically includes: Obtain the ideal value sequence of the ideal point through the corrected evaluation matrix; Calculate the Euclidean distance between all evaluation indicators of each sounding point in the fracturing section and the ideal value sequence; and The first model is specifically the following formula: Among them, the is the Euclidean distance between the depth measurement position x of the fracturing stage oi and the positive ideal value, and the Euclidean distance between the depth measurement position x of the fracturing stage oi and the negative ideal value, and the i d oi (x oi ) is the Euclidean distance between the depth measurement position x of the fracturing stage oi and the ideal value, and x oi is the depth corresponding to the i-th depth measurement point of the fracturing stage, is the value corresponding to in the evaluation matrix after correction.

8. An integrated evaluation device for implementing the integrated evaluation method according to any one of claims 1 to 7, characterized in that, Including: A data collection module, configured to obtain and store data of all evaluation indicators that can affect the fracturability of the reservoir; An evaluation indicator screening module, configured to screen the evaluation indicators in terms of geology and engineering according to the influence degree of each evaluation indicator on the fracturability; An evaluation matrix construction module, configured to construct an evaluation matrix considering all sounding points on the fracturing section; An evaluation matrix correction module, configured to correct the evaluation matrix according to the relationship between each evaluation indicator and the fracturability; A comprehensive evaluation model construction module, configured to calculate the distance between each sounding point and the ideal point according to the corrected evaluation matrix and the data of the evaluation indicators, and construct a comprehensive evaluation model for evaluating the fracturability; A visualization and reporting module, which generates a visual evaluation result according to the comprehensive evaluation model and generates an evaluation report.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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