A method and device for determining the type of well for a multi-layer tight sandstone gas reservoir

Abstract

The present application relates to a kind of multilayer system compact sandstone gas reservoir well type determination method and device, the method is carried out by the research block of compact sandstone gas reservoir to obtain gas well productivity evaluation result gas well production capacity evaluation;Again based on gas well productivity evaluation result, in combination with the geologic features of research area compact gas reservoir and fracturing construction factor, carry out single factor and multi-factor productivity influence factor analysis, determine gas well productivity main control geologic factor, strengthen the main control geologic factor analysis of the influence of gas well fracturing production effect, provide a kind of convenient quantifiable well type selection method.A series of different horizontal well straight well stimulation ratio corresponding well type optimization chart is established, for the first time, the numerical value of reserve concentration is reflected on the well type selection chart, which is convenient for well type selection in multilayer system compact gas reservoir. Realize the quantification of well type selection index, provide a basis for efficient and convenient well type selection, which has positive significance for improving reserve producing degree and development efficiency in compact gas reservoir.

Description

Technical Field

[0001] The invention relates to a method and device for determining a well type of a multi-layer tight sandstone gas reservoir. Background Art

[0002] Tight gas reservoirs have poor reservoir properties, small sand bodies, strong heterogeneity, and are characterized by low permeability, low abundance, and low yield. Tight gas reservoirs are widely distributed and have varying geological conditions. Some are marginally economical or uneconomical to develop. Improper well type selection can further reduce reserve recovery and economic benefits. To achieve optimal development results, the selection of development well types is crucial and plays a crucial role in improving gas reservoir development outcomes. Summary of the Invention

[0003] In order to provide a method for determining well types in multi-layer tight sandstone gas reservoirs, so that gas well selection indicators can be quantified and the reserve recovery and gas reservoir development effects can be maximized, the present invention proposes a method and device for determining well types in multi-layer tight sandstone gas reservoirs. The technical solutions proposed in the present invention are as follows:

[0004] In a first aspect, the present invention provides a method for determining a well type in a multi-layer tight sandstone gas reservoir, comprising:

[0005] Based on the pre-determined evaluation parameters, the gas well productivity evaluation is carried out in the study area of ​​tight sandstone gas reservoir to obtain the gas well productivity evaluation results;

[0006] Based on the gas well productivity evaluation results, and in accordance with the geological characteristics of the tight gas reservoir in the study area and the fracturing operation factors, the main controlling geological factors affecting the gas well productivity are determined; the main controlling geological factors include the total effective thickness of the reservoir and the reservoir permeability;

[0007] Based on the actual data of the gas field, a multi-layer tight gas reservoir numerical model is established;

[0008] Based on the multi-layer tight gas reservoir numerical model, the cumulative gas production of different well types under different reserves concentrations of horizontal well production layers and different combinations of controlling geological factors is calculated; wherein the well types include horizontal wells and vertical wells;

[0009] Based on the cumulative production of horizontal wells and vertical wells, calculate the production increase ratio under each combination of conditions;

[0010] For each of the predetermined different selected yield increase ratios:

[0011] According to the production increase ratio under each combination of conditions, the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration is calculated;

[0012] According to the reservoir permeability corresponding to the selected production increase ratio under the combination of different total effective reservoir thicknesses and reserve concentrations, the reservoir permeability corresponding to the selected reserve concentration under different total effective reservoir thicknesses is calculated, and a well type optimization chart is established;

[0013] According to the cost ratio of drilling horizontal wells and vertical wells in the planned drilling area, a corresponding target plate is selected from the well type optimization plates under all selected production increase ratios, and a target well type is determined based on the target plate.

[0014] In one or some embodiments, the calculation of the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration based on the production increase ratio under each combination of conditions includes:

[0015] For each combination of total effective thickness and reserve concentration of each reservoir in each combination of conditions:

[0016] According to the production increase multiples corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration, a second relationship between reservoir permeability and production increase multiples is obtained by fitting;

[0017] The reservoir permeability corresponding to the selected production increase ratio is calculated according to the second relationship.

[0018] In one or some embodiments, the second relationship between reservoir permeability and production increase ratio is obtained by fitting the production increase ratio corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration, including:

[0019] The production increase multiple data points corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration are selected, and trend line regression is performed on the data points using multiple methods. The trend line with the highest degree of fit is selected to obtain a second relationship between reservoir permeability and production increase multiple; wherein the multiple methods include: exponential regression, linear regression, logarithmic regression, polynomial regression and power function regression.

[0020] In one or some embodiments, the reservoir permeability corresponding to the selected reserve concentration under different total effective reservoir thicknesses is calculated by the following method:

[0021] For each of the different combinations of total effective thickness of reservoirs and reserve concentrations, the total effective thickness of each reservoir is:

[0022] Selecting reservoir permeability data points corresponding to different reserve concentrations under the total effective thickness of the reservoir, performing trend line regression on the data points, selecting the trend line with the highest fitting degree, and obtaining a first relationship between reservoir permeability and reserve concentration;

[0023] The reservoir permeability corresponding to the selected reserve concentration is calculated according to the first relationship.

[0024] In one or some embodiments, selecting a corresponding target plate from among all selected well type preferred plates under the production increase ratio according to the cost ratio between drilling horizontal wells and drilling vertical wells in the planned drilling area, and determining the target well type according to the target plate includes:

[0025] According to the cost ratio of drilling horizontal wells and vertical wells in the planned drilling area, the corresponding target plate is selected from the well type optimization plates under all selected production increase ratios;

[0026] According to the obtained effective thickness and permeability of the reservoir in the planned drilling area, points are placed in the target map;

[0027] Based on the obtained target layer reserve concentration in the planned drilling area, a corresponding reserve concentration curve is determined in the target plate;

[0028] The target well type is determined according to the position of the injection point relative to the reserve concentration curve.

[0029] In one or some embodiments, determining the target well type according to the position of the injection point relative to the reserve concentration curve includes:

[0030] If the injection point is below the reserve concentration curve, the target well type is a horizontal well; if the injection point is above the reserve concentration curve, the target well type is a vertical well.

[0031] In one or more embodiments, the method further comprises:

[0032] Obtaining the effective thickness of the reservoir in the planned drilling area, and determining whether the effective thickness of the reservoir in the planned drilling area meets the preset yield condition corresponding to the target well type;

[0033] If satisfied, the target well type is used as the final development well type.

[0034] In one or some embodiments, the multi-layer tight gas reservoir mathematical model is established by:

[0035] Obtaining gas field geological parameter data, gas reservoir fluid seepage-related data, and gas well production parameters from the actual gas field data; wherein the gas field geological parameter data include production layer distribution, gas reservoir porosity, permeability, and gas saturation; the gas reservoir fluid seepage-related data include gas density, water density, PVT data, gas-water relative permeability data, and rock compressibility; and the gas well production parameters include vertical wellbore location, horizontal wellbore location, vertical well production data, and horizontal well production data;

[0036] Based on the gas field geological parameter data, the gas reservoir fluid percolation related data and the gas well production parameter, a multi-layer tight gas reservoir numerical model is established.

[0037] Different reservoir permeability, different total effective thickness of reservoir, different horizontal well layer reserve concentration, different well type combination are selected to obtain the multi-layer tight gas reservoir numerical model of different well types under different reservoir conditions.

[0038] In one or some embodiments, the evaluation parameter includes gas well dynamic reserve; based on the pre-acquired evaluation parameter, the research block of the tight sandstone gas reservoir is carried out to obtain the gas well productivity evaluation result, including:

[0039] According to the production characteristics of the tight gas well in the research block, based on the preset gas well dynamic reserve evaluation method, the gas well dynamic reserve of the research block is determined, and the size of the gas well dynamic reserve of the single well is taken as the index of the long-term production capacity of the fractured well to obtain the gas well productivity evaluation result.

[0040] In the second aspect, the application provides a well type determination device for a multi-layer tight sandstone gas reservoir, including:

[0041] The evaluation module is used for carrying out the gas well production capacity evaluation based on the pre-determined evaluation parameter to obtain the gas well productivity evaluation result.

[0042] The analysis module is used for determining the main control geological factor affecting the gas well productivity according to the geological characteristics of the tight gas reservoir in the research block and the fracturing construction factors based on the gas well productivity evaluation result; the main control geological factor includes the total effective thickness of the reservoir and the reservoir permeability.

[0043] The modeling module is used for establishing the multi-layer tight gas reservoir numerical model according to the actual data of the gas field.

[0044] The first calculation module is used for calculating the cumulative gas production of different well types under different main control geological factor condition combinations under different horizontal well production layer reserve concentration based on the multi-layer tight gas reservoir numerical model; wherein, the well type includes the horizontal well and the vertical well.

[0045] The second calculation module is used for calculating the production increase ratio under each condition combination according to the horizontal well cumulative production and the vertical well cumulative gas production.

[0046] A chart establishment module is used to calculate, for each of the predetermined different selected production increase ratios, the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration, based on the production increase ratio under each combination of conditions; calculate the reservoir permeability corresponding to the selected reserve concentration under different total effective reservoir thicknesses, based on the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration, and establish a well type optimization chart;

[0047] The target well type determination module is used to select a corresponding target plate from all well type optimization plates under all selected production increase ratios based on the cost ratio of drilling horizontal wells to drilling vertical wells in the planned drilling area, and determine the target well type based on the target plate.

[0048] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for determining the well type of a multi-layer tight sandstone gas reservoir as described in the first aspect.

[0049] In a fourth aspect, the present invention provides an electronic device comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0050] Memory for storing computer programs;

[0051] The processor is configured to implement the method for determining the well type of a multi-layer tight sandstone gas reservoir as described in the first aspect when executing the program stored in the memory.

[0052] Based on the above technical solution, the present invention has the following beneficial effects compared with the prior art:

[0053] The present invention provides a method for determining well types in multi-layer tight sandstone gas reservoirs. This method evaluates the gas well production capacity of a study area of ​​the tight sandstone gas reservoir based on predetermined evaluation parameters to obtain a gas well productivity evaluation result. Based on the gas well productivity evaluation results, combined with the geological characteristics of the tight gas reservoir and fracturing operation factors in the study area, single-factor and multi-factor productivity influencing factors are analyzed to determine the primary geological factors controlling gas well productivity. This strengthens the analysis of the primary geological factors influencing post-fracturing gas well production performance, provides a convenient and quantifiable well type selection method, and addresses the shortcomings of existing methods. A series of well type optimization charts corresponding to different horizontal well and vertical well production increase ratios are established. For the first time, the numerical value of reserve concentration is reflected on the well type selection chart, facilitating well type selection in multi-layer tight gas reservoirs. Using the well type optimization chart, suitable well types can be determined based on the reservoir permeability, total effective reservoir thickness, and reserve concentration of the known formations. This quantifies the well type selection indicators, provides a basis for efficient and convenient well type selection, and has positive implications for improving reserve recovery and development efficiency in tight gas reservoirs.

[0054] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0055] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0057] Figure 1 This is a flow chart of a method for determining well types in multi-layer tight sandstone gas reservoirs;

[0058] Figure 2 This is a schematic diagram of the extremely poor results of various factors that affect the effect of fractured horizontal wells;

[0059] Figure 3 This is a schematic diagram showing the extremely poor results of various factors affecting the effect of fracturing vertical wells;

[0060] Figure 4 This is a schematic diagram of the model of fractured vertical wells and fractured horizontal wells in multi-layer tight gas reservoirs;

[0061] Figure 5 This is a curve showing the relationship between reservoir permeability and production increase ratio (total effective reservoir thickness is 12m, reserve concentration is 50%).

[0062] Figure 6 This is a curve showing the relationship between reservoir permeability and reserve concentration (total effective reservoir thickness is 12m);

[0063] Figure 7 This is a chart showing the optimal well type for different reserve concentrations (horizontal wells are 2.5 times more expensive than vertical wells);

[0064] Figure 8 This is the optimal chart for well types under different reserve concentrations (horizontal wells are 2.8 times more expensive than vertical wells);

[0065] Figure 9 This is a diagram of a preferred example of the well type W1-W4;

[0066] Figure 10 This is another flow chart of the method for determining the well type of a multi-layer tight sandstone gas reservoir;

[0067] Figure 11 This is a schematic diagram of the structure of a device for determining the well type of a multi-layer tight sandstone gas reservoir;

[0068] Figure 12 It is a structural diagram of an electronic device. DETAILED DESCRIPTION

[0069] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0070] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0071] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0072] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0073] At present, there are mainly the following methods for selecting well types: First, production capacity calculation is based on theoretical research and mathematical models, and the well type is selected from the perspective of maximum production capacity; second, a research area is selected, an actual geological model is established, numerical simulation is carried out, and the gas well indicators of different simulated well types are compared and analyzed to determine the well type; third, well type adaptability analysis is carried out from the perspective of development geology to determine the appropriate well type; fourth, gas well economic evaluation is carried out from the perspective of gas well controlled reserves and extraction costs to select the well type.

[0074] During their work, the inventors discovered several limitations in existing methods. Theoretical calculation models are complex, with numerous parameters, making accurate determination difficult and inconvenient for field use. Well type suitability analysis from a geological perspective often relies primarily on qualitative analysis, lacking quantitative evaluation. The modeling and numerical modeling process is complex and labor-intensive. Furthermore, economic evaluation methods lack convenient quantitative indicators for well type selection. These existing methods are not efficient and convenient for well type selection. Furthermore, they rely primarily on qualitative analysis, lack quantitative analysis, and lack quantifiable parameters for well type selection, falling short of the inventors' expectations. Further research and development led the inventors to the present invention.

[0075] In order to overcome the shortcomings of the existing technology, make the gas well selection indicators quantifiable, conveniently select well types through specific parameters, and maximize the reserve utilization and gas reservoir development effect, the present invention proposes a method and device for determining the well type of multi-layer tight sandstone gas reservoirs.

[0076] Example 1

[0077] The embodiment of the present invention provides a method for determining the well type of a multi-layer tight sandstone gas reservoir, referring toFigure 1 Shown, including:

[0078] S101. Based on pre-determined evaluation parameters, a gas well production capacity evaluation is performed on a study block of a tight sandstone gas reservoir to obtain a gas well productivity evaluation result;

[0079] Conducting gas well production capacity evaluation refers to addressing the uncertainty of the initial production of currently fractured gas wells by replacing open flow with dynamic reserves, which better reflects the long-term production capacity of fractured wells, as the key evaluation parameter. Post-fracture production capacity evaluation is conducted, and production forecasts are conducted throughout the life cycle of the gas well to understand the long-term production status of the gas well from the time it is opened to the time it is abandoned.

[0080] S102. Based on the gas well productivity evaluation results, and in accordance with the geological characteristics of the tight gas reservoir in the study area and fracturing operation factors, determine the main controlling geological factors affecting the gas well productivity; the main controlling geological factors include the total effective thickness of the reservoir and the reservoir permeability;

[0081] Determining the primary controlling geological factors of gas well productivity refers to selecting evaluation parameters that are both significantly impactful and independent of each other, with a minimum of factors selected to cover a wide range of attributes. Geological factors primarily include porosity, reservoir permeability, gas saturation, total effective reservoir thickness, reservoir length, effective reservoir length, and formation anisotropy. Using actual data, we conducted a single-factor analysis of factors influencing gas well productivity. Based on gas well and reservoir parameters, we established numerical models for fractured vertical and horizontal wells in typical tight gas reservoirs. Through single-factor data analysis and multi-factor orthogonal experimental analysis, we determined that the primary geological factors influencing gas well productivity are reservoir permeability and total effective reservoir thickness.

[0082] The quantitative determination of key geological parameters that affect the long-term production capacity of gas wells is mainly determined through multi-factor influencing factor analysis.

[0083] First, select the evaluation parameters.

[0084] The productivity of tight gas wells varies greatly, with numerous factors influencing productivity and complex relationships between them. It is impractical to identify all influencing factors, which necessitates the use of rational methods to screen out appropriate evaluation parameters, remove parameters with significant correlations, and identify the necessary key evaluation parameters. To select factors that significantly impact the productivity of fractured wells from a multitude of characteristic factors, several principles should be followed: first, the parameters must reflect a specific aspect, such as permeability reflecting flow capacity and porosity reflecting reservoir space; second, the selected parameter set must reflect as many key characteristics as possible. For example, for fractured horizontal wells, in addition to geological factors, fracture parameters related to fracture construction and parameters related to horizontal wells should also be included; third, the correlation between indicators is small and relatively independent; and fourth, the parameters must be easily accessible and quantifiable.

[0085] Screening was conducted according to the above principles, focusing on parameters that have a significant impact on fracturing gas wells and are independent of each other, and selecting as few factors as possible to cover as many attributes. For ease of analysis, based on actual data, the factors affecting production capacity were divided into two categories: geological and engineering, and analyzed to determine the main factors affecting production capacity. Geological factors mainly study porosity, reservoir permeability, gas saturation, total effective reservoir thickness, reservoir length, effective reservoir length, and formation anisotropy. Engineering factors mainly study horizontal section length, gas well skin coefficient, sand addition amount, fracture length, fracture conductivity, fracture spacing (number of stages), fracturing fluid return rate, and reservoir drilling rate.

[0086] Secondly, we conduct a single-factor analysis of factors influencing production capacity. This primarily involves analyzing the correlation between each selected evaluation parameter and dynamic reserves to determine which parameters have relatively high correlations and provide a preliminary assessment. The correlation between evaluation parameters and dynamic reserves can be calculated using a correlation function.

[0087] Finally, a multi-factor analysis of factors affecting gas well productivity was carried out. In the actual production process of gas wells, geological factors and engineering factors often interact with each other simultaneously. In order to study the main influencing factors of gas well productivity under the simultaneous interaction of different single factors, a numerical model of fractured horizontal wells in typical tight gas reservoirs was established based on the actual data of the Sulige gas field, and an orthogonal experiment was designed to analyze the primary and secondary order of the influence of different factors on gas well productivity.

[0088] The process for building numerical models for fractured vertical and horizontal wells in typical tight gas reservoirs is as follows. Eclipse, a commonly used numerical reservoir simulation software in the oil and gas field development industry, was used to build the model and perform simulations under different production parameters. The numerical simulation grid parameters for model development were 800 m in the x-direction, 1200 m in the y-direction, and 20 m in the z-direction, with a grid size of 20 × 20 × 1 m.

[0089] For fractured horizontal wells, based on the main influencing factors selected in the previous single-factor analysis, the reservoir permeability, total effective reservoir thickness, effective reservoir length, horizontal section length, number of fractures, and fracturing scale (fracture half-length) with relatively large influence were selected. At the same time, the fracture conductivity, horizontal well skin coefficient, and formation anisotropy were considered, and a 9-factor 4-level orthogonal experiment was designed. The horizontal well orthogonal experiment factors and their level values ​​are shown in Table 1.

[0090]

[0091] Table 1

[0092] Determine the range of each influencing factor separately, refer to Figure 2The following table shows the ranges of various factors affecting the effectiveness of horizontal well fracturing. Based on the ranges, the order of importance of their impact on horizontal well productivity is determined. See Table 2 for the results of the horizontal well range analysis.

[0093]

[0094] Table 2

[0095] The order of influence of various factors on the productivity of horizontal wells after fracturing is: reservoir permeability > number of fractures > fracture half-length > total effective reservoir thickness > Kv / Kh > effective reservoir length > horizontal section length > skin coefficient > conductivity.

[0096] For vertical wells, we selected reservoir permeability, total effective reservoir thickness, fracture half-length, fracture conductivity, vertical well skin coefficient, and formation anisotropy to design a six-factor, five-level orthogonal experiment. The factors and their levels for the vertical well orthogonal experiment are shown in Table 3 below.

[0097]

[0098] Table 3

[0099] Calculate the range of each factor that affects the effect of vertical fracturing wells separately. The results are as follows Figure 3 According to the range size, the order of importance of the impact on vertical well productivity is obtained. The vertical well range analysis results are shown in Table 4 below.

[0100]

[0101] Table 4

[0102] The order of influence of various factors on the productivity of vertical wells after fracturing is: reservoir permeability > total effective reservoir thickness > fracture half-length > Kv / Kh > skin coefficient > conductivity.

[0103] The above results show that the geological factors that have the greatest impact on the productivity of fractured vertical and horizontal wells in tight gas reservoirs are the total effective reservoir thickness and reservoir permeability. Therefore, the main controlling geological factors are the total effective reservoir thickness and reservoir permeability.

[0104] S103. Establish a multi-layer tight gas reservoir numerical model based on actual gas field data;

[0105] The multi-layer tight gas reservoir numerical model developed in this paper includes two types: a fractured vertical well production model and a fractured horizontal well production model. Vertical wells penetrate three strata, with perforation production in each stratum; horizontal wells produce only in stratum 3. Based on an analysis of factors influencing productivity and actual gas field data, a multi-layer tight gas reservoir numerical model was developed. The impact of varying controlling geological factors on the productivity of horizontal and vertical wells was compared and analyzed, thereby establishing a well type optimization chart for optimal well selection.

[0106] S104. Based on the multi-layer tight gas reservoir numerical model, calculate the cumulative gas production of different well types under different reserve concentrations of horizontal well production layers and different combinations of controlling geological factors; wherein the well types include horizontal wells and vertical wells;

[0107] Reserve concentration is the ratio of a single-layer geological reserves to the total reserves of the reservoir. Production increase ratio is the ratio of the cumulative gas production of horizontal wells to the cumulative gas production of vertical wells.

[0108] Based on the multi-layer tight gas reservoir numerical model, simulations are performed under different reservoir production conditions to obtain corresponding cumulative gas production. The different reservoir production conditions are the above-mentioned different horizontal well production layer reserve concentrations, total effective reservoir thickness and reservoir permeability combinations. The numerical range of the horizontal well production layer reserve concentration is determined based on the statistical value of the reservoir reserve concentration actually encountered by the horizontal wells in the area. The specific numerical range of the total effective reservoir thickness and reservoir permeability can be determined based on the main range of the reservoir physical property distribution in the study area. The calculation of the cumulative gas production is obtained by simulating different multi-layer tight gas reservoir numerical models with numerical simulation software. Based on the multi-layer tight gas reservoir numerical model established in step S103, the different horizontal well production layer reserve concentrations, total effective reservoir thickness and reservoir permeability in step S104 are arranged and combined to establish a corresponding number of models, and each model is simulated and calculated to obtain the cumulative gas production under different parameters.

[0109] S105. Calculate the production increase ratio under each condition combination based on the cumulative production of the horizontal wells and the cumulative gas production of the vertical wells;

[0110] The ratio of the cumulative gas production of horizontal wells to that of vertical wells is the production increase ratio. The above combination of conditions refers to the different combinations of reserve concentration in the production layer of horizontal wells, total effective reservoir thickness, and reservoir permeability.

[0111] S106. For each of the different predetermined selected production increase ratios:

[0112] According to the production increase ratio under each combination of conditions, the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration is calculated;

[0113] Based on the analysis of factors influencing productivity and actual gas field data, a multi-layer tight gas reservoir numerical model was established. The impact of changes in different controlling geological factors on the productivity of horizontal and vertical wells was compared and analyzed, thereby establishing a well type optimization chart and selecting the best well type. Based on the reservoir permeability corresponding to the selected production increase ratio under the combination of different total effective reservoir thickness and reserve concentration, the reservoir permeability corresponding to the selected reserve concentration under different total effective reservoir thickness was calculated, and a well type optimization chart was established;

[0114] In the establishment of the well type optimization chart, the reservoir permeability corresponding to a certain specific value of the stimulation ratio is calculated under different total effective reservoir thickness and reserve concentration; the relationship between the reservoir permeability and the reserve concentration when the stimulation ratio is a certain specific value under different total effective reservoir thickness is determined; the reservoir permeability corresponding to the reserve concentration in different intervals under different total effective reservoir thickness is determined according to the relationship between the reservoir permeability and the reserve concentration, and a chart is drawn to establish the well type optimization chart. By changing the value of the stimulation ratio, a series of charts under different stimulation ratios are obtained. The cost of the horizontal well and the cost of the vertical well are known for each condition combination of the well type optimization chart, that is, the cost ratio of the horizontal well to the vertical well is known. For each condition combination, the cost ratio under the condition combination is obtained, so as to correspond the cost ratio to the stimulation ratio, and a series of charts under different cost ratios of the horizontal well to the vertical well are obtained.

[0115] Referring to Figures 7 to 8 As shown in FIG. 2, the well type optimization charts under different reserve concentrations when the selected stimulation ratio is 2.5 and when the selected stimulation ratio is 2.8 are shown. The main parameters of the well type optimization chart are the total effective reservoir thickness, the reservoir permeability and the reserve concentration, which realizes the quantification of the well type selection parameters, and for the first time, the reserve concentration curve is applied to the well type optimization chart, which is convenient for the well type selection of the multi-layer tight gas reservoir.

[0116] S107, according to the cost ratio of drilling a horizontal well to drilling a vertical well in the area to be drilled, a corresponding target chart is selected from all the well type optimization charts under the selected stimulation ratio, and the target well type is determined according to the target chart.

[0117] Judging the suitable well type means that according to the reservoir permeability and the total effective reservoir thickness of the gas well wellpoint position, a corresponding point is found on the well type optimization chart, when the reserve concentration value of the gas well is below the reserve concentration curve on the chart, the horizontal well development is suitable; when the reserve concentration value of the gas well is above the reserve concentration curve on the chart, the vertical well development is suitable.

[0118] In an optional embodiment, the method further comprises:

[0119] S108, the reservoir effective thickness of the area to be drilled is obtained, and it is judged whether the reservoir effective thickness of the area to be drilled meets the preset yield condition corresponding to the target well type; if yes, the target well type is taken as the final development well type; if no, the development is suspended.

[0120] Economic benefit assessment refers to determining the lower limit of effective reservoir thickness for horizontal and vertical wells required to achieve a certain yield rate based on the effective reservoir thickness encountered by existing vertical and horizontal wells in the study area and EUR statistics. This assessment is based on whether the effective reservoir thickness in the proposed drilling area meets the corresponding lower limit. This economic benefit assessment is based on meeting the pre-determined yield rate for gas reservoir development, determining whether the development benefits meet the required level, and ultimately determining the final well type for gas reservoir development.

[0121] The present invention belongs to the field of oil and natural gas development, and particularly relates to a method for determining a well type for a multi-layer tight sandstone gas reservoir, which has important guiding significance for selecting a well type on-site in a gas field. The method overcomes the shortcomings of existing methods in that they are mainly based on qualitative analysis when selecting a well type, are insufficient in quantitative analysis, and are not convenient and fast enough. For a research block of a certain tight sandstone gas reservoir, a gas well production capacity evaluation is carried out, the main controlling factors of gas well production capacity are determined, a multi-layer tight gas reservoir numerical model is established, and single well indicators of vertical wells and horizontal wells are calculated and compared when different main controlling factors change. A series of well type optimization plates are established, and a suitable plate is selected according to the cost multiple of horizontal wells to vertical wells, and a suitable well type is judged. It is judged whether the economic benefits of the preferred well type meet the requirements, and the final development well type is determined. The present invention provides a convenient and quantifiable well type selection method, provides a basis for efficiently and conveniently selecting a well type, and has positive significance for improving the reserve utilization degree and improving the development efficiency of tight gas reservoirs.

[0122] Specifically, the present invention evaluates gas well production capacity in a study area of ​​tight sandstone gas reservoirs based on predetermined evaluation parameters to obtain gas well productivity evaluation results. Based on these evaluation results, combined with the geological characteristics of the tight gas reservoirs in the study area and fracturing operation factors, single-factor and multi-factor analyses of production capacity influencing factors are conducted to identify the primary controlling geological factors affecting gas well productivity. This strengthens the analysis of the primary controlling geological factors affecting post-fracturing gas well production outcomes, provides a convenient and quantifiable well type selection method, and addresses the shortcomings of existing methods. A series of well type optimization charts corresponding to different horizontal well and vertical well production increase ratios are established. For the first time, the numerical value of reserve concentration is reflected on the well type selection chart, facilitating well type selection for multi-layer tight gas reservoirs. Using the well type optimization chart, suitable well types can be determined based on the reservoir permeability, total effective reservoir thickness, and reserve concentration of known formations. This quantifies well type selection indicators, provides a basis for efficient and convenient well type selection, and has positive implications for improving reserve recovery and enhancing development efficiency in tight gas reservoirs.

[0123] In an optional embodiment, the evaluation parameters include dynamic reserves of the gas wells: the gas well productivity evaluation is performed on the study block of the tight sandstone gas reservoir based on the pre-acquired evaluation parameters to obtain the gas well productivity evaluation results, including:

[0124] According to the production characteristics of tight gas wells in the study area, based on the preset gas well dynamic reserve evaluation method, the dynamic reserves of gas wells in the study area are determined. The size of the gas well dynamic reserves of a single well is used as an indicator to evaluate the long-term production capacity of the fracturing well, and the gas well productivity evaluation result is obtained.

[0125] The production capacity of gas wells is evaluated. For tight gas reservoirs, the open flow rate varies greatly in different production stages. The single open flow rate comparison cannot accurately reflect the long-term production capacity of gas wells. By analyzing the dynamic reserves and the late production capacity of gas wells, dynamic reserves can better reflect the long-term production capacity of gas wells. The single-well controlled dynamic reserves are introduced as the main indicator for evaluating the long-term production effect of gas wells after fracturing. Based on this, the factors affecting gas well production capacity are analyzed and evaluated. The production characteristics of reservoirs and tight gas wells in the study area are as follows: (1) The reservoir is low in permeability and tight, and the pressure recovery time is long. There is a big contradiction between shut-in pressure measurement and gas field production, and there is a lack of pressure test data; (2) The production of gas wells varies greatly, and the stable production capacity of most wells is poor; (3) The production system of gas wells is unstable and the number of wells is large. Conventional dynamic reserve evaluation methods are difficult to fully apply. Based on the production characteristics of tight gas wells in the study area and the applicability of various methods, modern production instability analysis and production decline methods were selected as the primary methods for evaluating dynamic reserves of gas wells in the study area. The dynamic reserves of gas wells in the study area were determined, and the size of the dynamic reserves of individual wells was used as an indicator for evaluating the long-term production capacity of fractured wells. In the past, open flow rate was often used to evaluate gas well production capacity, but open flow rate does not represent long-term production capacity. A gas well with high initial open flow rate may not necessarily have high cumulative gas production later in life. The final cumulative gas production is the key measure of a gas well's long-term production capacity. Cumulative gas production can be obtained by multiplying the dynamic reserves by a preset coefficient. Based on the size, the larger the dynamic reserves of an individual well, the stronger the long-term production capacity of the fractured well.

[0126] In an optional embodiment, the multi-layer tight gas reservoir mathematical model is established by:

[0127] S1031. Acquire gas field geological parameter data, gas reservoir fluid seepage-related data, and gas well production parameters from the actual gas field data; wherein the gas field geological parameter data include production layer distribution, gas reservoir porosity, permeability, and gas saturation; the gas reservoir fluid seepage-related data include gas density, water density, PVT data, gas-water relative permeability data, and rock compressibility; and the gas well production parameters include vertical wellbore location, horizontal wellbore location, vertical well production data, and horizontal well production data;

[0128] The horizontal section length of the above-mentioned horizontal wells was obtained by calculating the average value of the horizontal section lengths of all wells in the study area.

[0129] S1032, establishing a multi-layer tight gas reservoir mathematical model based on the gas field geological parameter data, the gas reservoir fluid seepage related data, and the gas well production parameters;

[0130] S1033. Select different reservoir permeabilities, different total effective reservoir thicknesses, different horizontal well layer reserve concentrations, and different well type combinations to obtain numerical simulation models of multi-layer tight gas reservoirs with different well types under different reservoir conditions.

[0131] In an optional embodiment, the above step S106, based on the production increase ratio under each combination of conditions, calculates the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration, including:

[0132] For each combination of total effective thickness and reserve concentration of each reservoir in each combination of conditions:

[0133] S1061. According to the production increase multiples corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration, a second relationship between reservoir permeability and production increase multiples is obtained by fitting;

[0134] For example, when the total effective thickness of the reservoir is 12 m and the reserve concentration is 50%, the production increase multiple data points corresponding to different reservoir permeabilities when the total effective thickness of the reservoir is 12 m and the reserve concentration is 50% in step S104 are selected and fitted to obtain the second relationship between reservoir permeability and production increase multiple.

[0135] S1062. Calculate the reservoir permeability corresponding to the selected production increase ratio according to the second relationship.

[0136] Reservoir permeability calculation involves selecting existing data points for different permeability increase ratios, performing trendline regression on these data points (selecting the trendline with the highest fit, in this case, the power function with the highest fit). Using this regression equation, we determine the permeability for a specific increase ratio. Specifically, substituting the selected increase ratio into the second equation yields the corresponding reservoir permeability.

[0137] In an optional embodiment, the second relationship between reservoir permeability and production increase ratio is obtained by fitting the production increase ratio corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration, including:

[0138] Select the data points of the production increase ratio corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration, use multiple methods to perform trend line regression on the data points, select the trend line with the highest fitting degree, and obtain the second relationship between reservoir permeability and production increase ratio. Among them, the multiple methods include: exponential regression, linear regression, logarithmic regression, polynomial regression and power function regression. Figure 6 As shown in Figure 1, it is the relationship curve between reservoir permeability and reserve concentration when the total effective thickness of the reservoir is 12m and the reserve concentration is 50%.

[0139] The reservoir permeability corresponding to the selected reserve concentration under the different total effective reservoir thicknesses in step S106 is calculated as follows:

[0140] For each of the different combinations of total effective thickness of reservoirs and reserve concentrations, the total effective thickness of each reservoir is:

[0141] S201. Select reservoir permeability data points corresponding to different reserve concentrations under the total effective thickness of the reservoir, perform trend line regression on the data points, select the trend line with the highest fitting degree, and obtain a first relationship between reservoir permeability and reserve concentration.

[0142] The relationship between reservoir permeability and reserve concentration refers to selecting permeability data points corresponding to different reserve concentrations at different total reservoir effective thicknesses, performing trend line regression on the data points (selecting the trend line with the highest degree of fit, and in this case, the power function regression with the highest degree of fit), and obtaining a regression equation, which is the relationship between reservoir permeability and reserve concentration.

[0143] The above step S1061 determines the reservoir permeability corresponding to the selected production increase ratio for each combination of total effective thickness of the reservoir and reserve concentration. From the data set, for each total effective thickness of the reservoir, the reservoir permeability data points corresponding to different reserve concentrations under the total effective thickness of the reservoir are selected, and the first relationship between the reservoir permeability and reserve concentration under the total effective thickness of the reservoir is obtained by fitting. Figure 5 The figure shows the relationship between reservoir permeability and reserve concentration when the total effective reservoir thickness is 12 m. The present invention uses various fitting methods to perform trendline regression on selected data points. The trendline with the highest fit is selected to obtain a regression equation, which represents the relationship between reservoir permeability and reserve concentration. Fitting methods can include exponential regression, linear regression, logarithmic regression, polynomial regression, and power function regression.

[0144] S202. Calculate the reservoir permeability corresponding to the selected reserve concentration according to the first relationship.

[0145] Substituting the selected production increase times into the second relational equation, the corresponding reservoir permeability can be obtained by selecting the reserve concentration. According to the reservoir permeability corresponding to the selected reserve concentration under the total effective thickness of each reservoir, the corresponding well type optimization chart is established. Figure 8 As shown in the figure, it is the optimal well type chart under different reserve concentration when the production increase ratio is selected as 2.5.

[0146] In an optional embodiment, the above step S107, based on the cost ratio of drilling horizontal wells to drilling vertical wells in the planned drilling area, selects a corresponding target plate from the well type preferred plates under all selected production increase ratios, and determines the target well type based on the target plate, including:

[0147] S1071. Select a corresponding target plate from among all well type optimization plates under the selected production increase ratio according to the cost ratio of drilling a horizontal well to drilling a vertical well in the planned drilling area.

[0148] The horizontal well cost and vertical well cost of each condition combination used to establish the well type optimization map are known, that is, the horizontal well and vertical well cost ratio is known. For each condition combination, the cost ratio under the condition combination is obtained, so as to correspond the cost ratio with the selected production increase ratio. When selecting the target map of the planned drilling area, the well type optimization maps corresponding to the horizontal wells and vertical wells in the planned drilling area are screened from all the well type optimization maps under the selected production increase ratio to obtain the target map. Figure 7 and Figure 8 As shown in the figure, the well type optimization charts under different reserve concentrations are shown when the selected production increase ratio is 2.5 and the selected production increase ratio is 2.8.

[0149] S1072. Projecting a point on the target map based on the obtained effective reservoir thickness and reservoir permeability of the planned drilling area;

[0150] S1073. Based on the obtained reserve concentration of the target layer in the planned drilling area, determine a corresponding reserve concentration curve in the target plate;

[0151] S1074. Determine the target well type according to the position of the injection point relative to the reserve concentration curve.

[0152] In an optional embodiment, determining the target well type according to the position of the injection point relative to the reserve concentration curve includes:

[0153] If the injection point is below the reserve concentration curve, the target well type is a horizontal well; if the injection point is above the reserve concentration curve, the target well type is a vertical well.

[0154] Example 2

[0155] In order to make a clearer explanation of the well type determination method for multi-layer tight sandstone gas reservoirs provided by the embodiment of the present invention and verify the accuracy of the method, this embodiment will further illustrate the present invention with reference to the examples of four gas wells W1, W2, W3 and W4 in a multi-layer tight sandstone gas reservoir. Figure 10 As stated.

[0156] Step S301, conduct gas well production capacity evaluation. For tight gas reservoirs, the open flow rate varies greatly in different production stages. Using only the open flow rate for comparison cannot accurately reflect the long-term production capacity of the gas well. By analyzing the dynamic reserves and the late production capacity of the gas well, the dynamic reserves can better reflect the long-term production capacity of the gas well. The single-well controlled dynamic reserves are introduced as the main indicator for evaluating the long-term production effect after gas well fracturing. Based on this, the factors affecting gas well productivity are analyzed and evaluated. The production characteristics of reservoirs and tight gas wells in the study area are as follows: (1) The reservoir is low in permeability and tight, and the pressure recovery time is long. There is a big contradiction between shut-in pressure measurement and gas field production, and there is a lack of pressure test data; (2) The production of gas wells varies greatly, and the stable production capacity of most wells is poor; (3) The gas well production system is unstable and the number of wells is large. Conventional dynamic reserve evaluation methods are difficult to fully apply. According to the production characteristics of tight gas wells in the study area and the applicability analysis of various methods, the modern production instability analysis method and the production decline method are selected as the main methods for evaluating the dynamic reserves of gas wells in the study area. The dynamic reserves of gas wells in the study area are determined, and the size of the dynamic reserves of the gas wells in a single well is used as an indicator for evaluating the long-term production capacity of fracturing wells.

[0157] Step S302 analyzes the key geological factors controlling gas well productivity and identifies key geological parameters that influence the long-term production capacity of gas wells. Parameters that significantly impact fractured gas wells and are independent of each other are selected as evaluation parameters. Single-factor productivity influencing factor analysis is conducted using real-world data. Numerical models for fractured vertical and horizontal wells in typical tight gas reservoirs are established using gas well and reservoir parameters. Multi-factor productivity influencing factor analysis is conducted through orthogonal experiments. The results indicate that the geological factors most significantly impacting gas well productivity are total effective reservoir thickness and reservoir permeability. The process for determining key geological factors can be found in the description of S102 above and will not be repeated here.

[0158] Step S303: Based on the analysis of factors affecting productivity and actual data of the gas field, a multi-layer tight gas reservoir numerical model is established. The established model has three layers and includes two types: a fractured vertical well production model and a fractured horizontal well production model. The vertical wells penetrate the three layers and are perforated for production in each layer. The horizontal wells are only produced in layer 3 (refer to Figure 4 shown).

[0159] Eclipse, a numerical reservoir simulation software commonly used in oil and gas field development in the petroleum industry, was used for model development and simulation. This model was based on the relevant parameters of the Mizhi gas field, a typical multi-layer tight gas reservoir. The Mizhi gas field has multiple gas-bearing strata, with the primary formations being the He-8, Shan-2, and Taiyuan formations. The model developed for the field also includes three strata, divided into two scenarios: vertical well production with fractured wells and horizontal well production with fractured wells. In actual production, vertical wells penetrate all three strata, with perforations perforated throughout each stratum. Horizontal wells produce only in one stratum. The model also includes three strata, with vertical wells penetrating all three strata with perforations perforated throughout, and horizontal wells producing only in stratum 3. Eighteen horizontal wells are in production in the study area of ​​the gas field, with an average horizontal section length of approximately 1,100 meters and seven fractured sections. The modeled horizontal wells are 1,100 meters long and have seven fractured sections. We selected different combinations of reservoir permeabilities (six data points between 0.05 and 1 mD), total effective reservoir thicknesses (five data points between 4 and 20 m), horizontal well reserve concentrations (four data points between 25 and 100%), and well types (fractured vertical wells and horizontal wells) to develop a model with 6 × 5 × 4 × 2 = 240 wells. Production data for both horizontal and vertical wells under different reservoir conditions were obtained. The numerical simulation grid parameters for the model were 700 m in the x-direction, 2100 m in the y-direction, 50 m in the z-direction, and a grid size of 20 × 20 × 1 m.

[0160] Step S304 calculates the cumulative gas production of a single well for different controlling geological factors (reservoir permeability and total effective reservoir thickness) when the reservoir permeability is 0.05-1 mD, the total effective reservoir thickness is 4-20 m (the specific numerical range can be determined based on the main range of reservoir physical property distribution in the study area), and the horizontal well production layer reserve concentration is 25%-100%. For example, the calculated values ​​for this example are shown in the following table (Table 5). Based on the cumulative gas production of the horizontal wells and vertical wells, the production increase ratio for each combination of conditions is calculated.

[0161] Effective reservoir permeability (md) 0.05、0.2、0.4、0.6、0.8、1 Total effective reservoir thickness (m) 4、8、12、16、20 Horizon concentration of reserves in horizontal wells (%) 25、50、75、100 Well type Fractured vertical well, fractured horizontal well

[0162] Table 5

[0163] Cumulative gas production is calculated by simulating different models using numerical simulation software. Based on the multi-layer tight gas reservoir numerical model established in step S103, the parameters in Table 5 in step S304 are permuted and combined. The parameters include six different values ​​for reservoir permeability, five different values ​​for total effective reservoir thickness, four values ​​for reserve concentration, and two well types. A total of 6 × 5 × 4 × 2 = 240 models are established. Simulations are performed on each model to obtain cumulative gas production under different parameters.

[0164] In step S305, the cost of horizontal wells in the study area is 2.5 times that of vertical wells. The corresponding reservoir permeability is calculated when the production increase ratio is 2.5 under different total effective reservoir thicknesses and reserve concentrations. The production increase ratio value is selected based on the cost ratio of horizontal wells to vertical wells in the study area. For example, when the total effective thickness of the reservoir is 12m and the reserve concentration is 50%, the production increase ratio data points corresponding to different reservoir permeabilities when the total effective thickness of the reservoir is 12m and the reserve concentration is 50% in step S304 are selected (see Table 6), and trend line regression is performed on the data points. The trend line with the highest degree of fit is selected. The power function regression has the highest degree of fit this time (see Table 6). Figure 5 (as shown), the correlation coefficient reached 0.9854. Using the power function trendline regression formula, the corresponding reservoir permeability for a production increase ratio of 2.5 was calculated to be 0.102 mD. Using the same method, the corresponding reservoir permeability for a production increase ratio of 2.5 was calculated for the total effective thickness and reserve concentration of other reservoirs. This yielded the corresponding reservoir permeability for a production increase ratio of 2.5 for each reservoir's total effective thickness and reserve concentration.

[0165] In step S304, Table 1 shows five values ​​of total effective reservoir thickness: 4, 8, 12, 16, and 20. There are four different values ​​for horizontal well stratum reserve concentration. There are 5×4=20 combinations of different total effective reservoir thickness and horizontal well stratum reserve concentration. Each data combination corresponds to a reservoir permeability calculation formula, and there are 20 calculation formulas in total. One of the 20 combinations is selected here as an example for explanation, that is, the calculation of reservoir permeability when the total effective reservoir thickness is 12m and the reserve concentration is 50%. Through the explanation in the example, the power function regression is obtained, referring to Figure 5 As shown, Figure 5 The power function formula from the regression is the formula for calculating reservoir permeability. Substituting the production increase ratio into the formula as x, the calculated y value is the reservoir permeability corresponding to that production increase ratio. Similarly, for each combination, regressing the data points yields a power function formula, which serves as the reservoir permeability calculation formula for the other cases.

[0166]

[0167] Table 6

[0168] Step S306 , calculating the reservoir permeability corresponding to the reserve concentration when the production increase ratio is 2.5 under different effective reservoir thicknesses.

[0169] First, determine the relationship between reservoir permeability and reserve concentration when the production increase ratio is 2.5 under different effective reservoir thicknesses. Select the reservoir permeability data points corresponding to the different reserve concentrations obtained in step S305 under different total effective reservoir thicknesses, and perform trend line regression on the data points to obtain the result. For example, when the total effective reservoir thickness is 12m, select the reservoir permeability data points (Table 7) corresponding to the production increase ratio of 2.5 for the different reserve concentrations obtained in step S305, perform trend line regression on the data points, and select the trend line with the highest degree of fit. The trend line with the highest degree of fit this time is the power function regression (refer to Figure 6 (as shown), with a correlation coefficient of 0.9993. This power function regression equation represents the relationship between reservoir permeability and reserve concentration. This formula calculates the corresponding reservoir permeability for a total effective reservoir thickness of 12m and a reserve concentration ranging from 5% to 100%. Similarly, by regressing the reserve concentration-permeability curve for other total effective reservoir thicknesses, we can obtain the corresponding reservoir permeability for other total effective reservoir thicknesses and reserve concentrations ranging from 5% to 100%.

[0170]

[0171] Table 7

[0172] Graphs were drawn using Excel, and trend lines were added to the data points. The trend line options included exponential, linear, logarithmic, polynomial, and power. Each regression method was tried, and the correlation coefficient R-squared values ​​of various regressions were compared. The power function regression had the highest correlation coefficient.

[0173] Step S307: Create a chart based on the data points of reservoir permeability and reserve concentration under different total effective reservoir thicknesses obtained in step S306. Figure 7 As shown, this is the well type selection chart when the cost of a horizontal well is 2.5 times that of a vertical well (i.e., the production increase ratio).

[0174] Step S308: Change the production increase multiple to obtain a series of charts for different horizontal well to vertical well cost multiples. For example, by varying the production increase multiple from 2.1, 2.2, and gradually increasing to 3.0, a series of charts are obtained for horizontal wells where the cost of the vertical well is 2.1, 2.2, and finally 3.0 times that of the horizontal well. Figure 8 This is the well type selection chart when the cost of a horizontal well is 2.8 times that of a vertical well.

[0175] Step S309, select the appropriate chart based on the horizontal well and vertical well cost ratio to determine the appropriate well type. According to the reservoir permeability and total effective reservoir thickness of the gas well, find the corresponding point on the chart. When the reserve concentration value of the gas well is at the lower left of the corresponding reserve concentration curve on the chart, it is suitable for horizontal well development; when it is at the upper right of the curve, it is suitable for vertical well development. The parameters of W1-W4 wells are shown in Table 8. Mark W1-W4 wells on the chart according to the total effective reservoir thickness and reservoir permeability values ​​(refer to Figure 9 As shown in the figure, Well W1, where horizontal wells are planned to be deployed, has a reserve concentration of 57%. The data point for Well W1 is located above and to the right of the 57% reserve concentration line. Based on the chart, Well W1 is suitable for vertical well deployment. Similarly, Well W2, where horizontal wells are planned to be deployed, has a reserve concentration of 48%. The data point for Well W2 is located above and to the right of the 48% reserve concentration line. Based on the chart, Well W2 is suitable for vertical well deployment. Well W3, where horizontal wells are planned to be deployed, has a reserve concentration of 59%. The data point for Well W3 is located below and to the left of the 59% reserve concentration line. Based on the chart, Well W3 is suitable for horizontal well deployment. Well W4, where horizontal wells are planned to be deployed, has a reserve concentration of 73%. The data point for Well W4 is located below and to the left of the 73% reserve concentration line. Based on the chart, Well W4 is suitable for horizontal well deployment.

[0176]

[0177] Table 8

[0178] Step S310, economic benefit judgment. Determine whether the well type determined according to the map can meet a certain preset rate of return condition and determine whether to adopt this well type for development. According to the effective reservoir thickness and EUR statistics of the vertical and horizontal wells drilled in this study area, a rate of return of 6% is achieved. The effective reservoir thickness of horizontal wells is generally above 8m, and the effective reservoir thickness of vertical wells is generally above 12m. The total effective reservoir thickness of Well W1 is 7m, less than 12m, which does not meet the preset rate of return condition. The development benefit does not meet the requirements and is suitable for postponing development; the total effective reservoir thickness of Well W2 is 15.8m, greater than 12m, which meets the preset rate of return condition and is suitable for vertical well development; the effective reservoir thickness of the layer where the horizontal well is planned to be deployed in Well W3 is 7.85m, less than 8m, which does not meet the preset rate of return condition. The development benefit does not meet the requirements and is suitable for postponing development; the effective reservoir thickness of the layer where the horizontal well is planned to be deployed in Well W4 is 14.45m, greater than 8m, which meets the internal rate of return condition and is suitable for horizontal well development.

[0179] Example 3

[0180] The embodiment of the present invention provides a device for determining the well type of a multi-layer tight sandstone gas reservoir, referring to Figure 11 Shown, including:

[0181] Evaluation module 401 is used to evaluate the gas well productivity of the research block of the tight sandstone gas reservoir based on predetermined evaluation parameters to obtain a gas well productivity evaluation result;

[0182] An analysis module 402 is configured to determine, based on the gas well productivity evaluation results, the main controlling geological factors affecting the gas well productivity according to the geological characteristics of the tight gas reservoir in the study area and the fracturing operation factors; the main controlling geological factors include the total effective thickness of the reservoir and the reservoir permeability;

[0183] Modeling module 403, used to establish a multi-layer tight gas reservoir numerical model based on actual gas field data;

[0184] A first calculation module 404 is configured to calculate, based on the multi-layer tight gas reservoir numerical model, the cumulative gas production of different well types under different reserves concentrations of production layers of horizontal wells and different combinations of controlling geological factors; wherein the well types include horizontal wells and vertical wells;

[0185] The second calculation module 405 is used to calculate the production increase ratio under each condition combination based on the cumulative production of the horizontal well and the cumulative gas production of the vertical well;

[0186] A chart creation module 406 is configured to calculate, for each of the predetermined different selected production increase ratios, the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration, based on the production increase ratio under each combination of conditions; calculate the reservoir permeability corresponding to the selected reserve concentration under different total effective reservoir thicknesses, based on the reservoir permeability corresponding to the selected production increase ratio under the different combinations of total effective reservoir thickness and reserve concentration, and create a well type optimization chart;

[0187] The target well type determination module 407 is used to select a corresponding target plate from the well type preferred plates under all selected production increase ratios according to the cost ratio of drilling horizontal wells to drilling vertical wells in the planned drilling area, and determine the target well type according to the target plate.

[0188] In an optional embodiment, the device further comprises:

[0189] The judgment module 408 is used to obtain the effective thickness of the reservoir in the planned drilling area and judge whether the effective thickness of the reservoir in the planned drilling area meets the preset yield condition corresponding to the target well type; if so, the target well type is used as the final development well type.

[0190] The implementation principle and technical effects of the device for determining the well type of a multi-layer tight sandstone gas reservoir provided in an embodiment of the present invention are similar to those of any of the aforementioned method embodiments and will not be repeated here.

[0191] Example 4

[0192] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the method for determining the well type of a multi-layer tight sandstone gas reservoir as described in any of the aforementioned method embodiments is implemented.

[0193] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments, or may exist independently without being incorporated into the device / apparatus. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0194] According to an embodiment of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0195] Example 5

[0196] An embodiment of the present invention provides an electronic device, referring to Figure 12 As shown, it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114.

[0197] Memory 113, for storing computer programs;

[0198] The processor 111 is configured to implement the method for determining the well type of a multi-layer tight sandstone gas reservoir described in any one of the aforementioned method embodiments when executing the program stored in the memory 113 .

[0199] The implementation principle and technical effects of the electronic device provided by the embodiment of the present invention are similar to those of any of the aforementioned method embodiments and will not be repeated here.

[0200] The memory 113 can be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk, or a ROM. The memory 113 has storage space for program code for executing any of the method steps described above. For example, the storage space for program code can include individual program codes for implementing each of the steps in the method described above. These program codes can be read from or written to one or more computer program products. These computer program products include program code carriers such as a hard disk, a compact disc (CD), a memory card, or a floppy disk. Such computer program products are typically portable or fixed storage units. The storage unit can have storage segments or storage space arranged similarly to the memory 113 in the electronic device described above. The program code can be compressed, for example, in a suitable form. Typically, the storage unit includes a program for executing the method steps according to an embodiment of the present invention, i.e., code that can be read by, for example, the processor 111, and when executed by the electronic device, causes the electronic device to execute the various steps in the method described above.

[0201] In this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article or apparatus. The orientation or positional relationship indicated by the terms "upper", "lower", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0202] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention is not limited to any single aspect, nor to any single embodiment, nor to any combination and / or permutation of these aspects and / or embodiments. Each aspect and / or embodiment of the present invention can be used alone or in combination with one or more other aspects and / or other embodiments.

[0203] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for determining the well type of a multi-layer tight sandstone gas reservoir, characterized in that: include: Based on the pre-determined evaluation parameters, the gas well productivity evaluation is carried out in the study area of ​​tight sandstone gas reservoir to obtain the gas well productivity evaluation results; Based on the gas well productivity evaluation results, and in accordance with the geological characteristics of the tight gas reservoir in the study area and the fracturing operation factors, the main controlling geological factors affecting the gas well productivity are determined; the main controlling geological factors include the total effective thickness of the reservoir and the reservoir permeability; Based on the actual data of the gas field, a multi-layer tight gas reservoir numerical model is established; Based on the multi-layer tight gas reservoir numerical model, the cumulative gas production of different well types under different reserves concentrations of horizontal well production layers and different combinations of controlling geological factors is calculated; wherein the well types include horizontal wells and vertical wells; Based on the cumulative production of horizontal wells and vertical wells, calculate the production increase ratio under each combination of conditions; For each of the predetermined different selected yield increase ratios: According to the production increase ratio under each combination of conditions, the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration is calculated; According to the reservoir permeability corresponding to the selected production increase ratio under the combination of different total effective reservoir thicknesses and reserve concentrations, the reservoir permeability corresponding to the selected reserve concentration under different total effective reservoir thicknesses is calculated, and a well type optimization chart is established; According to the cost ratio of drilling horizontal wells and vertical wells in the planned drilling area, a corresponding target plate is selected from the well type preferred plates under all selected production increase ratios, and a target well type is determined based on the target plate.

2. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 1, characterized in that: The step of calculating the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration according to the production increase ratio under each combination of conditions includes: For each combination of total effective thickness and reserve concentration of each reservoir in each combination of conditions: According to the production increase multiples corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration, a second relationship between reservoir permeability and production increase multiples is obtained by fitting; The reservoir permeability corresponding to the selected production increase ratio is calculated according to the second relationship.

3. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 2, characterized in that: The second relationship between reservoir permeability and production increase ratio is obtained by fitting the production increase ratio corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration, including: The production increase multiple data points corresponding to different reservoir permeabilities under the combination of the total effective thickness of the reservoir and the reserve concentration are selected, and trend line regression is performed on the data points using multiple methods. The trend line with the highest degree of fit is selected to obtain a second relationship between reservoir permeability and production increase multiple; wherein the multiple methods include: exponential regression, linear regression, logarithmic regression, polynomial regression and power function regression.

4. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 1, wherein: The reservoir permeability corresponding to the selected reserve concentration under the different total effective reservoir thicknesses is calculated by the following method: For each of the different combinations of total effective thickness of reservoirs and reserve concentrations, the total effective thickness of each reservoir is: Selecting reservoir permeability data points corresponding to different reserve concentrations under the total effective thickness of the reservoir, performing trend line regression on the data points, selecting the trend line with the highest fitting degree, and obtaining a first relationship between reservoir permeability and reserve concentration; The reservoir permeability corresponding to the selected reserve concentration is calculated according to the first relationship.

5. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 1, characterized in that: The method of selecting a target plate from among all selected well type optimization plates under the selected production increase ratio according to the cost ratio between drilling horizontal wells and drilling vertical wells in the planned drilling area, and determining the target well type according to the target plate includes: According to the cost ratio of drilling horizontal wells and vertical wells in the planned drilling area, the corresponding target plate is selected from the well type optimization plates under all selected production increase ratios; According to the obtained effective thickness and permeability of the reservoir in the planned drilling area, points are placed in the target map; Based on the obtained target layer reserve concentration in the planned drilling area, a corresponding reserve concentration curve is determined in the target plate; The target well type is determined according to the position of the injection point relative to the reserve concentration curve.

6. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 5, characterized in that: Determining the target well type according to the position of the injection point relative to the reserve concentration curve includes: If the injection point is below the reserve concentration curve, the target well type is a horizontal well; if the injection point is above the reserve concentration curve, the target well type is a vertical well.

7. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 1, characterized in that: The method further comprises: Obtaining the effective thickness of the reservoir in the planned drilling area, and determining whether the effective thickness of the reservoir in the planned drilling area meets the preset yield condition corresponding to the target well type; If satisfied, the target well type is used as the final development well type.

8. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 1, wherein: The multi-layer tight gas reservoir numerical model is established in the following way: Obtaining gas field geological parameter data, gas reservoir fluid seepage-related data, and gas well production parameters from the actual gas field data; wherein the gas field geological parameter data include production layer distribution, gas reservoir porosity, permeability, and gas saturation; the gas reservoir fluid seepage-related data include gas density, water density, PVT data, gas-water relative permeability data, and rock compressibility; and the gas well production parameters include vertical wellbore location, horizontal wellbore location, vertical well production data, and horizontal well production data; Establishing a multi-layer tight gas reservoir numerical model based on the gas field geological parameter data, the gas reservoir fluid seepage related data and the gas well production parameters; By selecting different reservoir permeabilities, different total effective reservoir thicknesses, different horizontal well reserve concentrations, and different well type combinations, numerical simulation models of multi-layer tight gas reservoirs with different well types under different reservoir conditions were obtained.

9. The method for determining the well type of a multi-layer tight sandstone gas reservoir according to claim 8, characterized in that: The evaluation parameters include the dynamic reserves of the gas wells. The gas well productivity evaluation results obtained by conducting a gas well productivity evaluation on the study block of the tight sandstone gas reservoir based on the pre-acquired evaluation parameters include: According to the production characteristics of tight gas wells in the study area, based on the preset gas well dynamic reserve evaluation method, the dynamic reserves of gas wells in the study area are determined. The size of the gas well dynamic reserves of a single well is used as an indicator to evaluate the long-term production capacity of the fracturing well, and the gas well productivity evaluation result is obtained.

10. A device for determining the well type of a multi-layer tight sandstone gas reservoir, characterized in that: include: An evaluation module is used to evaluate the gas well production capacity of a research block of a tight sandstone gas reservoir based on predetermined evaluation parameters to obtain a gas well productivity evaluation result; An analysis module is configured to determine, based on the gas well productivity evaluation results, the main controlling geological factors affecting the gas well productivity according to the geological characteristics of the tight gas reservoir in the study area and the fracturing operation factors; the main controlling geological factors include the total effective thickness of the reservoir and the reservoir permeability; Modeling module, used to establish a multi-layer tight gas reservoir numerical model based on actual gas field data; A first calculation module is configured to calculate, based on the multi-layer tight gas reservoir numerical model, the cumulative gas production of different well types under different reserve concentrations of production layers of horizontal wells and different combinations of controlling geological factors; wherein the well types include horizontal wells and vertical wells; The second calculation module is used to calculate the production increase ratio under each condition combination based on the cumulative production of horizontal wells and the cumulative gas production of vertical wells; A chart establishment module is used to calculate, for each of the predetermined different selected production increase ratios, the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration, based on the production increase ratio under each combination of conditions; calculate the reservoir permeability corresponding to the selected reserve concentration under different total effective reservoir thicknesses, based on the reservoir permeability corresponding to the selected production increase ratio under different combinations of total effective reservoir thickness and reserve concentration, and establish a well type optimization chart; The target well type determination module is used to select a corresponding target plate from all well type optimization plates under all selected production increase ratios based on the cost ratio of drilling horizontal wells to drilling vertical wells in the planned drilling area, and determine the target well type based on the target plate.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for determining the well type of a multi-layer tight sandstone gas reservoir according to any one of claims 1 to 9 is implemented.

12. An electronic device, characterized in that: The processor, the communication interface, the memory and the communication bus are connected to each other via the communication bus. Memory for storing computer programs; The processor is configured to implement the method for determining the well type of a multi-layer tight sandstone gas reservoir according to any one of claims 1 to 9 when executing the program stored in the memory.

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