Tight gas reservoir well pattern adjusting and optimizing method, device and equipment

Abstract

The invention discloses a tight gas reservoir well pattern adjustment optimization method, device and equipment, and the method comprises the steps: determining the layered static reserves of each development layer series in a well pattern adjustment region based on the reservoir parameters of the tight gas reservoir well pattern adjustment region; based on the current development condition of the tight gas reservoir well pattern adjustment area, determining the layered dynamic reserve of each development layer series in the well pattern adjustment area; based on the layered static reserves and the layered dynamic reserves of all the development layer series in the well pattern adjusting area, the layered dynamic and static reserve ratio and the unused reserve concentration degree of all the development layer series in the well pattern adjusting area are determined; determining a well spacing variation coefficient of each development layer series in the well pattern adjustment area based on the coordinates of the existing gas well in the well pattern adjustment area and the development layer series corresponding to the gas well; and optimizing and adjusting the tight gas reservoir well pattern based on the layered dynamic and static reserve ratio, the unused reserve concentration ratio and the well spacing variation coefficient of each development layer series in the well pattern adjustment area. According to the method, the residual reserves and well pattern distribution of the tight gas reservoir are evaluated in a layer-by-layer and classified manner.

Description

Technical Field

[0001] This invention relates to the field of tight gas reservoir development and design technology, and in particular to a method, apparatus and equipment for adjusting and optimizing the well pattern of a tight gas reservoir. Background Technology

[0002] Tight sandstone gas reservoirs are one of the main types of gas reservoirs for natural gas development. They are characterized by deep and thin reservoirs (deep burial and thin reservoir thickness), low reserve abundance, tight reservoirs, and strong heterogeneity. Compared with conventional gas reservoirs, their single-well controlled reserves are lower and decline more rapidly. Therefore, how to improve the recovery rate of tight gas has become the core issue for maintaining stable production and efficient development of gas fields. Well densification is an effective means to improve the recovery rate of tight gas reservoirs, as verified by domestic and international development practices. However, with the increase in development level, the remaining reserves between wells and between layers become fragmented, making potential tapping difficult. Developing more refined well network adjustment strategies is key to further improving the utilization of reserves. Summary of the Invention

[0003] In order to improve the overall recovery rate of tight gas reservoirs, enhance the degree of reserve control of gas wells over each development layer, and thus enrich technical routes and increase the selection space, this invention provides a method, apparatus and equipment for adjusting and optimizing tight gas reservoir well network.

[0004] In a first aspect, embodiments of the present invention provide a method for adjusting and optimizing the well pattern of a tight gas reservoir, which may include:

[0005] Based on the reservoir parameters of the tight gas reservoir well network adjustment zone, the stratified static reserves of each development layer in the well network adjustment zone are determined.

[0006] Based on the current development conditions of the tight gas reservoir well network adjustment area, the dynamic reserves of each development layer in the well network adjustment area are determined.

[0007] Based on the stratified static and stratified dynamic reserves of each development layer in the well network adjustment area, the stratified dynamic-static reserve ratio and the concentration of untapped reserves of each development layer in the well network adjustment area are determined.

[0008] Based on the coordinates of existing gas wells in the well network adjustment area and the corresponding development layers of the gas wells, the well spacing variation coefficient of each development layer in the well network adjustment area is determined.

[0009] Based on the ratio of dynamic and static reserves, concentration of undeveloped reserves, and well spacing variation coefficient of each development layer in the well network adjustment area, the well network of tight gas reservoirs is optimized and adjusted.

[0010] In one embodiment, optimizing the tight gas reservoir well network based on the dynamic-static reserve ratio, untapped reserve concentration, and well spacing variation coefficient of each development layer in the well network adjustment area may include:

[0011] Compare the concentration of unused reserves in each development layer with the preset concentration threshold.

[0012] If the concentration of unused reserves is greater than the concentration threshold, the corresponding development layer is determined to be the target of regional well network optimization and adjustment, and horizontal wells are densified for the development layer in combination with regional geological conditions and effective sand body distribution characteristics.

[0013] If the concentration of untapped reserves is not greater than the concentration threshold, then the well network optimization and adjustment scheme for each development layer is determined based on the dynamic-static reserve ratio and well spacing variation coefficient of each development layer.

[0014] In another embodiment, if the concentration of undeveloped reserves is not greater than the concentration threshold, then determining the well network optimization and adjustment scheme for each development layer based on the dynamic-static reserve ratio and well spacing variation coefficient of each development layer may include:

[0015] A cross-sectional chart was constructed based on the ratio of dynamic and static reserves in each development layer and the coefficient of variation of well spacing.

[0016] Cluster analysis was performed based on the intersection chart to determine the classification boundary parameters of the stratified dynamic and static reserve ratios and the coefficient of variation of well spacing for all development strata in the well network adjustment area.

[0017] Based on the reserve ratio classification boundary parameter and the coefficient of variation classification boundary parameter, the types of each development layer are classified; if the dynamic and static reserve ratio of the development layer is less than the reserve ratio classification boundary parameter, it is determined that the development layer is an imperfect regional well network, and the well network of the development layer is densified.

[0018] If the dynamic-static reserve ratio of the development layer is not less than the reserve ratio classification limit parameter, and the well spacing variation coefficient of the development layer is greater than the variation coefficient classification limit parameter, then it is determined that the well network distribution of the development layer is uneven, and the well network of the development layer is densified.

[0019] If the dynamic-to-static reserve ratio of the development layer is not less than the reserve ratio classification limit parameter, and the well spacing variation coefficient of the development layer is not greater than the variation coefficient classification limit parameter, then the well network of the development layer is judged to be complete and evenly distributed. The development layer is densified by means of local densification adjustment, layer checking and hole filling, or old well sidetracking, or the low-yield and low-efficiency gas wells of the development layer are improved by repeated fracturing.

[0020] In another embodiment, determining the stratified dynamic reserves of each development layer in the well network adjustment zone based on the current development conditions of the tight gas reservoir well network adjustment zone may include:

[0021] Based on the current development conditions of the tight gas reservoir well network adjustment area, the final recoverable reserves and dynamic reserves of each well under the existing development well network of the tight gas reservoir are determined using the tight gas well dynamic analysis method.

[0022] Based on the final recoverable reserves and dynamic reserves of each well in the existing development well network of the tight gas reservoir, the stratified dynamic reserves of each development layer in the well network adjustment area are determined by the production capacity splitting method.

[0023] In another embodiment, determining the well spacing variation coefficient of each development layer in the well network adjustment area based on the coordinates of existing gas wells and the corresponding development layers of the gas wells may include:

[0024] The coordinates of all gas wells within the well network adjustment area are determined, and the development layer of each gas well is determined through perforation data.

[0025] Based on the coordinates of the gas well and the corresponding development layer, the well spacing of each development layer in the well network adjustment area is determined;

[0026] Based on the well spacing of each development layer in the well pattern adjustment area, the mean and standard deviation of the well spacing of each development layer in the well pattern adjustment area are determined.

[0027] Based on the mean and standard deviation of well spacing of each development layer in the well network adjustment area, the coefficient of variation of well spacing of each development layer in the well network adjustment area is determined.

[0028] In a second aspect, embodiments of the present invention provide a tight gas reservoir well network design method, which may include: designing a well network of gas wells based on the tight gas reservoir well network optimization scheme obtained by the tight gas reservoir well network adjustment and optimization method described in the first aspect.

[0029] Thirdly, embodiments of the present invention provide a tight gas reservoir well pattern adjustment and optimization device, which may include:

[0030] The static reserves determination module is used to determine the stratified static reserves of each development layer in the well network adjustment area based on the reservoir parameters of the tight gas reservoir well network adjustment area.

[0031] The dynamic reserve determination module is used to determine the stratified dynamic reserves of each development layer in the tight gas reservoir well network adjustment area based on the current development conditions of the well network adjustment area.

[0032] The dynamic-static reserve ratio and concentration module is used to determine the dynamic-static reserve ratio and untapped reserve concentration of each development layer in the well network adjustment area based on the layered static reserves and layered dynamic reserves of each development layer in the well network adjustment area.

[0033] The variation coefficient determination module is used to determine the well spacing variation coefficient of each development layer in the well network adjustment area based on the coordinates of existing gas wells and the development layers corresponding to the gas wells.

[0034] The optimization and adjustment module is used to optimize and adjust the tight gas reservoir well network based on the dynamic and static reserve ratio of each development layer, the concentration of unutilized reserves, and the well spacing variation coefficient in the well network adjustment area.

[0035] Fourthly, embodiments of the present invention provide a tight gas reservoir well network design device, which may include: a design module, used to design a well network of gas wells according to the tight gas reservoir well network optimization and adjustment scheme obtained by the tight gas reservoir well network adjustment and optimization method described in the first aspect.

[0036] Fifthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the tight gas reservoir well network adjustment and optimization method as described in the first aspect, or implements the tight gas reservoir well network design method as described in the second aspect.

[0037] In a sixth aspect, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the tight gas reservoir well network adjustment and optimization method as described in the first aspect, or implements the tight gas reservoir well network design method as described in the second aspect.

[0038] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0039] This invention provides a method, apparatus, and equipment for adjusting and optimizing the well network of a tight gas reservoir. This method combines existing well network constraints with dynamic and static data to evaluate the remaining reserves and well network distribution of tight gas reservoirs layer by layer and by type, and formulates a more detailed method for deploying infill wells. The results are of great significance for the development evaluation of tight gas reservoirs, the adjustment of development plans, and the formulation of detailed strategies to improve recovery rates.

[0040] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0041] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0042] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0043] Figure 1 This is a flowchart of the tight gas reservoir well pattern adjustment and optimization method provided in this embodiment of the invention;

[0044] Figure 2 Here is a flowchart showing the specific execution process of step S15;

[0045] Figure 3 This is an example of a selected block well area provided in an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram of the clustering classification in step S1531;

[0047] Figure 5 This is a diagram illustrating the well pattern adjustment and optimization effect provided in an embodiment of the present invention.

[0048] Figure 6 This is a schematic diagram of the tight gas reservoir well network adjustment and optimization device provided in an embodiment of the present invention. Detailed Implementation

[0049] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0050] Currently, the common method for deploying infill wells mainly evaluates the infill potential of a block by establishing the relationship between well network density, the final expected recovery rate, and reserve abundance. Patent CN112031757A further adds economic limit constraints to determine the infill potential and degree of infill within a region. However, the inventors found in practice that this method usually only provides an overall well network density suggestion for the target block, lacking specific strategies for well network infill and well location deployment. Patent CN111622733A introduces a more refined gridded method for evaluating remaining reserves and infill, achieving a more refined evaluation of remaining reserves by dividing the block into grids. However, the inventors also found in practice that tight gas reservoirs are highly heterogeneous and have poor connectivity. Early development well networks are mostly concentrated in reserve-rich areas, with irregular well network layouts. This method lacks evaluation of existing well networks and analysis of differentiated well network infill strategies, thus lacking effective guidance for infill well deployment.

[0051] Furthermore, based on practical experience and analysis of existing literature, the inventors believe that as gas reservoir development deepens, the number of development layers increases, and remaining reserves become fragmented, improving the overall recovery rate of the gas reservoir necessitates increasing the degree of reserve control of gas wells over each development layer. Therefore, evaluating the reserve utilization level and well network conditions by layer is particularly important. In summary, establishing a well network densification method that can classify layers by type and comprehensively consider dynamic and static data and well network conditions is a current technical requirement for formulating reasonable enhanced oil recovery strategies for tight gas reservoirs. In view of the above problems, this invention is proposed to provide a method, apparatus, and equipment for adjusting and optimizing the well network in tight gas reservoirs to overcome or at least partially solve the above problems.

[0052] This invention provides a method for adjusting and optimizing the well pattern of a tight gas reservoir, referring to... Figure 1 As shown, the method may include the following steps:

[0053] Step S11: Based on the reservoir parameters of the tight gas reservoir well network adjustment zone, determine the stratified static reserves of each development layer in the well network adjustment zone.

[0054] This step involves calculating the static reserves (layered static reserves) of each development stratum within a selected well network adjustment zone in a tight gas reservoir. After determining the study area, this step identifies the main development strata of the block based on regional geological information; then, the gas-bearing area A of each development stratum is calculated. i Porosity φ i Permeability k, gas saturation S gi Reservoir temperature T i reservoir pressure (P) i and P sc ), original gas deviation coefficient Z i Based on parameters such as volumetric efficiency, the geological reserves (also known as static reserves) of each stratum in the study area are calculated using the volumetric method (Formula 1). Formula 1 is as follows:

[0055]

[0056] in,' i Geological reserves, in billions of cubic meters, with the subscript 'i' representing a small layer (development layer); A i For air-bearing area, km 2 ,;h i φ represents the gas layer thickness in meters (m); i Porosity; S gi The original gas saturation; P i and P sc These are the initial formation pressure and the standard surface pressure, respectively, in MPa; T i and T sc These are, respectively, formation temperature and surface standard temperature, in K; Z. i This represents the original gas deviation coefficient.

[0057] Step S12: Based on the current development conditions of the tight gas reservoir well network adjustment zone, determine the dynamic reserves of each development layer in the well network adjustment zone.

[0058] Under existing well network development conditions, evaluate the dynamic-to-static reserve ratio and the concentration of remaining reserves in each layer within the evaluation area. It should be noted that in this embodiment of the invention, steps S11 and S12 are not performed in any particular order; step S11 can be performed before step S12, or step S12 can be performed before step S11, or both steps S11 and S12 can be performed simultaneously. This embodiment of the invention does not impose specific limitations on this.

[0059] In practice, the final recoverable reserves and dynamic reserves of each well in the existing development well network of the tight gas reservoir are determined first based on the current development conditions of the tight gas reservoir well network adjustment area using the tight gas well dynamic analysis method. Then, based on the final recoverable reserves and dynamic reserves of each well in the existing development well network of the tight gas reservoir, the dynamic reserves of each development layer in the well network adjustment area are determined using the production capacity partitioning method.

[0060] The above-mentioned capacity partitioning method in this embodiment of the invention can specifically be the capacity coefficient method, and the stratified dynamic reserves of each development layer can be calculated according to formula (2) as follows:

[0061]

[0062] Where, k i G represents the permeability of layer i; D G represents the total dynamic reserves of the study area (well network adjustment area) and the sum of the dynamic reserves of each development layer. D =∑G Di , Yifang; G Di The dynamic reserves of the i-th development layer.

[0063] Step S13: Based on the stratified static and stratified dynamic reserves of each development layer in the well network adjustment area, determine the stratified dynamic-static reserve ratio and the concentration of unutilized reserves of each development layer in the well network adjustment area.

[0064] In this step, based on the static and dynamic reserves of each development stratum, the ratio of static to dynamic reserves R of each development stratum is calculated. i It can be calculated using the following formula (3):

[0065] R i =G Di / G i Formula (3)

[0066] Unutilized reserves concentration F iDefined as the proportion of untapped reserves in each well network within a region to the total untapped reserves in the region, i.e.:

[0067]

[0068] Among them, G i -G Di Let G be the remaining reserves of the i-th smallest layer. i -G Di ) represents the total remaining reserves of the block.

[0069] The dynamic-to-static reserve ratio reflects the degree of reserve utilization of the current well network in the development zone. A higher dynamic-to-static ratio indicates larger well-controlled reserves and a higher degree of well network perfection. The concentration of untapped reserves reflects the distribution of remaining reserves in each development zone within the area. Understanding this parameter helps identify the main layers for tapping remaining reserves and formulate reasonable well network adjustment plans.

[0070] Step S14: Based on the coordinates of existing gas wells in the well network adjustment area and the corresponding development layers of the gas wells, determine the well spacing variation coefficient of each development layer in the well network adjustment area.

[0071] This step evaluates the uniformity and degree of well network distribution in each development layer of the well network adjustment area using the well spacing variation coefficient. It should be noted that in this embodiment of the invention, steps S11-S13 and S14 are not executed in any particular order. Steps S11-S13 can be executed before step S14, or step S14 can be executed before steps S11-S13, or steps S13 and S14 can be executed simultaneously, as long as the above steps are performed before step S15. This embodiment of the invention does not impose specific limitations on this.

[0072] In practice, the first step is to collect the coordinates of all gas wells in the well network adjustment area and determine the development layer of each gas well through perforation data. The second step is to determine the well spacing of each development layer in the well network adjustment area based on the coordinates of the gas wells and the corresponding development layer. The third step is to determine the mean and standard deviation of the well spacing of each development layer in the well network adjustment area based on the well spacing of each development layer. Finally, the coefficient of variation of the well spacing of each development layer in the well network adjustment area is determined based on the mean and standard deviation of the well spacing.

[0073] Specifically, firstly, the coordinates of all gas wells in the region are statistically analyzed. The development layer of each gas well is determined using perforation data, and the well spacing of each development layer is clarified. The mean (μ) and standard deviation (σ) of the well spacing for each layer in the region are then statistically calculated using the following formula (5):

[0074] μ=mean({L j,min ,…,L n,min}),σ=Stdev({L j,min ,…,L n,min}) Formula (5)

[0075] Among them, L j,min This represents the shortest distance between gas well j and its adjacent gas wells.

[0076] The mean value reflects the well network density of the area; a larger mean value indicates a lower well network density, and vice versa. The standard deviation characterizes the uniformity of the well network distribution; the more irregular the well spacing, the larger the standard deviation, which to some extent reflects the well placement strategy of the priority enrichment areas in the early development. The well spacing variation coefficient is defined as the ratio of the standard deviation to the mean value. It is dimensionless and reflects the uniformity of the well network distribution, eliminating the influence of the area of ​​the adjustment zone for different well networks and establishing a unified classification standard. The well spacing variation coefficient is calculated according to formula (6) as follows:

[0077] VMR=σ / μ Formula (6)

[0078] Step S15: Based on the dynamic-to-static reserve ratio, untapped reserve concentration, and well spacing variation coefficient of each development layer in the well network adjustment area, optimize and adjust the well network of the tight gas reservoir. This step evaluates the reserves and well network conditions of each development layer in the study area based on the untapped reserve concentration, dynamic-to-static reserve ratio, and well spacing variation coefficient, and formulates well network adjustment strategies for each development layer.

[0079] The tight gas reservoir well network adjustment and optimization method provided in this embodiment of the invention combines existing well network constraints with dynamic and static data to evaluate the remaining reserves and well network distribution of tight gas reservoirs layer by layer and by type, and formulate a more detailed method for deploying infill wells. The results are of great significance for the development evaluation of tight gas reservoirs, the adjustment of development plans, and the formulation of detailed strategies to improve recovery rate.

[0080] In an optional embodiment, step S15 above optimizes and adjusts the tight gas reservoir well network based on the dynamic-static reserve ratio, unexploited reserve concentration, and well spacing variation coefficient of each development layer in the well network adjustment zone, referring to... Figure 2 As shown, the specific steps may include:

[0081] Step S151: Compare the concentration of undeveloped reserves in each development layer with the preset concentration threshold. If the concentration of undeveloped reserves is greater than the concentration threshold, proceed to step S152; otherwise, if the concentration of undeveloped reserves is not greater than the concentration threshold, proceed to step S153. Step S152: Determine the corresponding development layer as the target for regional well network optimization and adjustment, and intensify horizontal wells in the development layer based on regional geological conditions and effective sand body distribution characteristics. Step S153: Determine the well network optimization and adjustment scheme for each development layer based on the dynamic and static reserve ratio and well spacing variation coefficient of each development layer.

[0082] In practical implementation, the aforementioned preset concentration threshold can be set to 70%. For strata (layers) with an undeveloped reserve concentration greater than 70%, they are classified as Type A. That is, when undeveloped reserves are concentrated in a single stratum (well network undeveloped reserve concentration > 70%), this stratum can be identified as the main target for regional well network adjustment. Considering regional geological conditions and the effective sand body distribution characteristics, horizontal well infill drilling is recommended to fully tap the remaining reserves between strata and improve the utilization rate of vertical reserves. For strata with an undeveloped reserve concentration of no more than 70%, considering the dynamic-to-static reserve ratio and well spacing variation coefficient of each stratum, targeted well network optimization and adjustment schemes are specified for each development stratum.

[0083] In a specific embodiment, step S153 described above may specifically include the following steps when executed:

[0084] Step S1531: Construct an intersection chart based on the ratio of dynamic and static reserves in each development layer and the coefficient of variation of well spacing.

[0085] Step S1532: Perform cluster analysis based on the intersection chart to determine the classification boundary parameters of the stratified dynamic and static reserve ratios and the coefficient of variation of well spacing for all development layers in the well network adjustment area.

[0086] Step S1533: Classify the types of each development layer based on the reserve ratio classification limit parameter and the coefficient of variation classification limit parameter; if the dynamic-static reserve ratio of the development layer is less than the reserve ratio classification limit parameter, proceed to step S1534; if the dynamic-static reserve ratio of the development layer is not less than the reserve ratio classification limit parameter, and the well spacing coefficient of variation of the development layer is greater than the coefficient of variation classification limit parameter, proceed to step S1535; if the dynamic-static reserve ratio of the development layer is not less than the reserve ratio classification limit parameter, and the well spacing coefficient of variation of the development layer is not greater than the coefficient of variation classification limit parameter, proceed to step S1536.

[0087] Step S1534: Determine that the development layer has an incomplete regional well network, and densify the well network for the development layer.

[0088] Step S1535: Determine that the well network distribution of the development layer is uneven, and densify the well network of the development layer;

[0089] Step S1536: Determine that the well network of the development layer is complete and evenly distributed. Then, increase the density of the development layer by means of local densification adjustment, layer checking and hole filling, or side-drilling of old wells. Alternatively, improve the low-yield and inefficient gas wells of the development layer by means of repeated fracturing.

[0090] In this embodiment of the invention, clustering analysis methods (such as the K-means clustering algorithm) are used to determine classification boundary parameters, thereby defining classification standards for different types of well areas within the well network adjustment area (study area), and formulating differentiated well network densification strategies based on the classification results. In this embodiment of the invention, well areas of type B, type C, and type D can be classified using the aforementioned classification boundary parameters, as detailed below:

[0091] Type B: Dynamic-to-static ratio is less than the reserve ratio classification threshold parameter (parameter a): The regional well network is incomplete, the development level is low, the reserves are not fully utilized, and there are many remaining reserves. For this type of area, it is suitable to use a reasonable well network density to deploy infill wells in the favorable development area in one go, thereby improving the utilization rate of reserves.

[0092] Type C areas, where the dynamic-to-static ratio is greater than the reserve ratio classification threshold parameter (parameter a) and the coefficient of variation is greater than the coefficient of variation classification threshold parameter (parameter b), have a significant amount of untapped reserves. Influenced by the previous "first develop the rich, then the poor" development strategy, the well network distribution is uneven, the coefficient of variation is large, and there is still considerable room for infill drilling. In these areas, diagonal infill drilling between wells can be implemented, taking into account regional geological characteristics and existing well network deployment, to further improve reserve control.

[0093] Type D: When the dynamic-to-static ratio is greater than the reserve ratio classification threshold parameter (parameter a) and the coefficient of variation is less than the coefficient of variation classification threshold parameter (parameter b): This type of area typically has a relatively complete well network, with gas wells evenly distributed and remaining reserves scattered, but there is still some potential for further development. Well areas with a long development history often belong to this type. The remaining reserves in this category are mostly inter-well reserves. Combining the geological characteristics of the layer, reserve distribution, and existing well network conditions, methods such as local infill drilling, layer checking and perforation, or sidetracking of old wells can be used to further tap the remaining potential and improve reserve utilization. For some low-yield and inefficient wells, repeated fracturing can be used to increase the EUR of a single well, further improving the recovery rate.

[0094] In a specific example, the main target layers of a gas field are the Lower Shihezi Formation 8 (He 8 Member) and the Shanxi Formation 1 (Shan 1 Member) of the Upper Paleozoic Era. These are onshore braided river deposits, with the effective reservoirs mainly consisting of braided mid-channel bars and coarse-grained deposits at the bottom of braided channels, representing typical low-permeability to tight sandstone gas reservoirs. A well network infiltration strategy analysis was conducted in a selected block, using the method provided in the embodiments of the present invention as follows:

[0095] (1) Select 25 well areas within the block (e.g., Figure 3 As shown in the figure, the dynamic and static data of each well area are compiled. First, the development strata and static parameters of each layer are determined. The main gas-producing layers in this area are He8 and Shan1. Based on geological and logging information, the reservoir thickness, gas-bearing area, porosity, gas saturation, temperature, pressure, gas compressibility factor, etc. of the two sub-layers can be determined respectively. The geological reserves of each well area and each sub-layer are calculated according to the volumetric method.

[0096] (2) Organize regional dynamic data and determine regional dynamic and static parameters. There are a total of 1706 wells in the region. The correspondence between development layers and gas wells is determined based on perforation information. Production dynamic analysis is carried out on each well to determine dynamic reserves and perform stratification. The dynamic reserves of each well in each layer are calculated to obtain the stratified dynamic reserves of the well area. Then, the dynamic-static reserve ratio and the concentration of unutilized reserves in the well network are calculated according to Equations 3 and 4. Then, the well spacing in each well area is statistically analyzed, and its mean and standard deviation are calculated according to Equation 5 to obtain the coefficient of variation (VMR). A total of 50 sets of statistical data for 25 well areas and 2 development layers are shown in Table 1, including parameters such as well density, dynamic-static ratio, concentration of unutilized reserves in the well network, and coefficient of variation.

[0097] Table 1. Statistical Table of Parameters for Two Development Layers

[0098]

[0099]

[0100] (3) Classification based on the concentration of undeveloped reserves in each layer. Layers with high concentration (greater than 70%) are classified as Type A, allowing for the development of more horizontal wells. For example, in well area 11 of this case, the concentration of undeveloped reserves in section 8 is as high as 78%, with undeveloped reserves reaching 1.85 billion cubic meters. Therefore, when formulating infill strategies, a larger network of horizontal wells can be deployed in section 8, such as... Figure 5 As shown in Figure a. It should be noted that this invention... Figure 5 The Class I, Class II, Class III, and Class IV reserves, corresponding to reserves of different grades, can play an auxiliary role in the well pattern adjustment in the embodiments of the present invention. Those skilled in the art should not misunderstand them. Figure 5 The interpretation is somewhat misunderstanding.

[0101] (4) Cluster the remaining data (unexploited reserves concentration <70%), determine standard classification parameters, and analyze and plot the cross-plot of dynamic-static ratio and coefficient of variation. Through the data analysis in this example, the cutoff points for dynamic-static ratio and coefficient of variation were determined to be a = 25% and b = 0.25, respectively. Based on this, the stratigraphic units (referring to a specific layer in the well area) in this region can be divided into three types, such as... Figure 4 As shown, the coefficient of variation decreases and well network conditions improve with increasing utilization. The following countermeasures and infill well deployment suggestions can be made for different types of strata:

[0102] Type B: Dynamic-to-static ratio less than 25%. This type of formation has poor development and a large amount of untapped reserves. A typical well area is Well Area 1. Figure 5 As shown in Figure b, the dynamic-to-static ratio of layer 8 in this well area is only 19%, the remaining reserves are abundant, and there are few gas wells with a large coefficient of variation.

[0103] Based on a detailed reservoir description, these types of formations can be deployed in a single, integrated well network using a combination of vertical and horizontal wells, employing a more uniform well layout to improve the degree of reserve control.

[0104] Type C: Dynamic-to-static ratio > 25%, VMR > 0.25. This type has a large stratigraphic variation coefficient, uneven well network distribution, and still has a significant amount of remaining reserves, offering considerable potential for infill drilling. A typical well area of ​​this type is Well Area 19. Figure 5 As shown in Figure c, the dynamic-static ratio of the He8 section in this well area is relatively high at 43.55%, the well network variation coefficient is 0.25, the distribution is relatively uneven, and about 67% of the remaining reserves in this well area are concentrated in the He8 section, indicating that there is still potential for infill drilling.

[0105] For these types of formations, diagonal well densification can be used to further increase the density and uniformity of the well network, thereby improving the overall reserve control and utilizing untapped reserves. The specific well placement can be based on the dynamic and static data of each formation, and new wells should be drilled to connect as many formations as possible to improve the overall reserve control.

[0106] Type D: Dynamic-to-static ratio > 25%, VMR < 0.25. This type of formation has a relatively complete and evenly distributed well network; remaining reserves are scattered, but there is still some room for infill drilling and potential tapping. Well areas with longer development histories often belong to this type. In this example, a typical well area is Well Area 15. Figure 5 As shown in Figure d, section 8 of the well area remains the main layer for potential tapping, with a high dynamic-to-static ratio of about 47%, numerous gas wells, and a uniform distribution, with a coefficient of variation of 0.19.

[0107] For these types of well areas, infiltration can be carried out by combining geological characteristics, reserve distribution, and well network distribution characteristics. This can be achieved through methods such as local infiltration adjustment, layer checking and hole filling, or sidetracking of old wells. Alternatively, repeated fracturing can be used to increase the EUR of a single well for low-yield and inefficient wells, thereby further improving the degree of reserve control.

[0108] (5) By conducting detailed descriptions of the remaining reserves and well network conditions in the block well area and layer by layer, more refined and reasonable strategies for improving the recovery rate of the combined layer and the deployment of infill wells can be formulated based on the various indicators and classifications of the He8 section and Shan1 section in the same well area. This also reflects the superiority of this method.

[0109] The tight gas reservoir well network adjustment and optimization method provided in this embodiment of the invention comprehensively considers various geological and development factors, such as the concentration of uncontrolled reserves, the distribution of remaining reserves, and the characteristics of the existing well network. It quantifies and refines these factors down to each development layer, meticulously evaluates the infill potential of each development layer, and provides corresponding well network infill methods. The dynamic and static data required by this method are abundant in oilfields, easily obtainable, and simple to calculate. The evaluation indicators used are comprehensive, reasonable, and easy to implement, effectively helping to evaluate tight gas reservoir well networks, formulate well network adjustment strategies, and implement infill well deployment.

[0110] Based on the same inventive concept, this embodiment of the invention also provides a tight gas reservoir well network design method, including: designing a well network of gas wells according to the tight gas reservoir well network optimization and adjustment scheme obtained by the above-mentioned tight gas reservoir well network adjustment and optimization method.

[0111] Based on the same inventive concept, this invention also provides a tight gas reservoir well pattern adjustment and optimization device, referring to... Figure 6 As shown, it may include: a static reserve determination module 61, a dynamic reserve determination module 62, a dynamic-static reserve ratio and concentration determination module 63, a coefficient of variation determination module 64, and an optimization adjustment module 65. Its working principle is as follows:

[0112] The static reserves determination module 61 is used to determine the stratified static reserves of each development layer in the well network adjustment area based on the reservoir parameters of the tight gas reservoir well network adjustment area.

[0113] The dynamic reserve determination module 62 is used to determine the stratified dynamic reserves of each development layer in the well network adjustment area based on the current development conditions of the tight gas reservoir well network adjustment area.

[0114] The dynamic-static reserve ratio and concentration determination module 63 is used to determine the dynamic-static reserve ratio and untapped reserve concentration of each development layer in the well network adjustment area based on the layered static and dynamic reserves of each development layer in the well network adjustment area.

[0115] The variation coefficient determination module 64 is used to determine the well spacing variation coefficient of each development layer in the well network adjustment area based on the coordinates of existing gas wells and the development layers corresponding to the gas wells.

[0116] The optimization and adjustment module 65 is used to optimize and adjust the tight gas reservoir well network based on the dynamic and static reserve ratio of each development layer, the concentration of undeveloped reserves, and the well spacing variation coefficient in the well network adjustment area.

[0117] In an optional embodiment, the optimization adjustment module 65 is specifically used for:

[0118] Compare the concentration of unused reserves in each development layer with the preset concentration threshold.

[0119] If the concentration of unused reserves is greater than the concentration threshold, the corresponding development layer is determined to be the target of regional well network optimization and adjustment, and horizontal wells are densified for the development layer in combination with regional geological conditions and effective sand body distribution characteristics.

[0120] If the concentration of untapped reserves is not greater than the concentration threshold, then the well network optimization and adjustment scheme for each development layer is determined based on the dynamic-static reserve ratio and well spacing variation coefficient of each development layer.

[0121] In an optional embodiment, the optimization and adjustment module 65 is further configured to:

[0122] A cross-sectional chart was constructed based on the ratio of dynamic and static reserves in each development layer and the coefficient of variation of well spacing.

[0123] Cluster analysis was performed based on the intersection chart to determine the classification boundary parameters of the stratified dynamic and static reserve ratios and the coefficient of variation of well spacing for all development strata in the well network adjustment area.

[0124] Based on the reserve ratio classification boundary parameter and the coefficient of variation classification boundary parameter, the types of each development layer are classified; if the dynamic and static reserve ratio of the development layer is less than the reserve ratio classification boundary parameter, it is determined that the development layer is an imperfect regional well network, and the well network of the development layer is densified.

[0125] If the dynamic-static reserve ratio of the development layer is not less than the reserve ratio classification limit parameter, and the well spacing variation coefficient of the development layer is greater than the variation coefficient classification limit parameter, then it is determined that the well network distribution of the development layer is uneven, and the well network of the development layer is densified.

[0126] If the dynamic-to-static reserve ratio of the development layer is not less than the reserve ratio classification limit parameter, and the well spacing variation coefficient of the development layer is not greater than the variation coefficient classification limit parameter, then the well network of the development layer is judged to be complete and evenly distributed. The development layer is densified by means of local densification adjustment, layer checking and hole filling, or old well sidetracking, or the low-yield and low-efficiency gas wells of the development layer are improved by repeated fracturing.

[0127] In an optional embodiment, the dynamic reserve determination module 62 described above is specifically used for:

[0128] Based on the current development conditions of the tight gas reservoir well network adjustment area, the final recoverable reserves and dynamic reserves of each well under the existing development well network of the tight gas reservoir are determined using the tight gas well dynamic analysis method.

[0129] Based on the final recoverable reserves and dynamic reserves of each well in the existing development well network of the tight gas reservoir, the stratified dynamic reserves of each development layer in the well network adjustment area are determined by the production capacity splitting method.

[0130] In an optional embodiment, the above-mentioned coefficient of variation determination module 64 is specifically used for:

[0131] The coordinates of all gas wells within the well network adjustment area are determined, and the development layer of each gas well is determined through perforation data.

[0132] Based on the coordinates of the gas well and the corresponding development layer, the well spacing of each development layer in the well network adjustment area is determined;

[0133] Based on the well spacing of each development layer in the well pattern adjustment area, the mean and standard deviation of the well spacing of each development layer in the well pattern adjustment area are determined.

[0134] Based on the mean and standard deviation of well spacing of each development layer in the well network adjustment area, the coefficient of variation of well spacing of each development layer in the well network adjustment area is determined.

[0135] Based on the same inventive concept, this embodiment of the invention also provides a tight gas reservoir well network design device, including: a design module, used to design a well network of gas wells according to the tight gas reservoir well network optimization and adjustment scheme obtained by the above-mentioned tight gas reservoir well network adjustment and optimization method.

[0136] Based on the same inventive concept, this embodiment of the invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-mentioned tight gas reservoir well network adjustment and optimization method, or implements the above-mentioned tight gas reservoir well network design method.

[0137] Based on the same inventive concept, this embodiment of the invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-mentioned tight gas reservoir well network adjustment and optimization method, or implements the above-mentioned tight gas reservoir well network design method.

[0138] The principles by which the above-mentioned devices, media, and related equipment in the embodiments of the present invention solve the problem are similar to those of the aforementioned methods. Therefore, their implementation can refer to the implementation of the aforementioned methods, and repeated details will not be repeated.

[0139] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0140] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0141] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0142] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0143] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for optimizing well pattern adjustment in a tight gas reservoir, characterized in that, The method comprises the following steps: determining the static reserves of each development layer in the well pattern adjustment area of the tight gas reservoir based on the reservoir parameters of the well pattern adjustment area; determining the dynamic reserves of each development layer in the well pattern adjustment area of the tight gas reservoir based on the current development conditions of the well pattern adjustment area; determining the dynamic-static reserve ratio and the unexploited reserve concentration of each development layer in the well pattern adjustment area based on the static reserves and the dynamic reserves of each development layer in the well pattern adjustment area; determining the well spacing variation coefficient of each development layer in the well pattern adjustment area based on the coordinates of the existing gas wells in the well pattern adjustment area and the development layers corresponding to the gas wells; optimizing and adjusting the well pattern of the tight gas reservoir based on the dynamic-static reserve ratio, the unexploited reserve concentration and the well spacing variation coefficient of each development layer in the well pattern adjustment area.

2. The method of claim 1, wherein, The step of optimizing and adjusting the well pattern of the tight gas reservoir based on the dynamic-static reserve ratio, the unexploited reserve concentration and the well spacing variation coefficient of each development layer in the well pattern adjustment area comprises the following steps: comparing the unexploited reserve concentration of each development layer with a preset concentration threshold value; if the unexploited reserve concentration is greater than the concentration threshold value, judging that the corresponding development layer is the object of regional well pattern optimization adjustment, and adding horizontal wells to the development layer in combination with the regional geological conditions and the effective sand body distribution characteristics; if the unexploited reserve concentration is not greater than the concentration threshold value, determining the well pattern optimization adjustment scheme for each development layer based on the dynamic-static reserve ratio and the well spacing variation coefficient of each development layer.

3. The method of claim 2, wherein, The step of determining the well pattern optimization adjustment scheme for each development layer based on the dynamic-static reserve ratio and the well spacing variation coefficient of each development layer if the unexploited reserve concentration is not greater than the concentration threshold value comprises the following steps: constructing an intersection chart based on the dynamic-static reserve ratio and the well spacing variation coefficient of each development layer; performing cluster analysis based on the intersection chart to determine the reserve ratio classification limit parameter and the variation coefficient classification limit parameter corresponding to the dynamic-static reserve ratio and the well spacing variation coefficient of all development layers in the well pattern adjustment area; classifying the types of each development layer based on the reserve ratio classification limit parameter and the variation coefficient classification limit parameter; if the dynamic-static reserve ratio of a development layer is less than the reserve ratio classification limit parameter, judging that the well pattern of the development layer is imperfect, and adding wells to the development layer; if the dynamic-static reserve ratio of a development layer is not less than the reserve ratio classification limit parameter, and the well spacing variation coefficient of the development layer is greater than the variation coefficient classification limit parameter, judging that the well pattern of the development layer is unevenly distributed, and adding wells to the development layer; if the dynamic-static reserve ratio of a development layer is not less than the reserve ratio classification limit parameter, and the well spacing variation coefficient of the development layer is not greater than the variation coefficient classification limit parameter, judging that the well pattern of the development layer is perfect and evenly distributed, and adding wells to the development layer by means of local densification adjustment, layer checking and hole supplementing or old well sidetracking, or improving the low-yield and low-efficiency gas wells of the development layer by means of repeated fracturing.

4. The method of claim 1, wherein, The step of determining the dynamic reserves of each development layer in the well pattern adjustment area of the tight gas reservoir based on the current development conditions of the well pattern adjustment area comprises the following steps: Based on the current development conditions of the well pattern adjustment area of the tight gas reservoir, the final recoverable reserves and dynamic reserves of each well under the existing well pattern of the tight gas reservoir are determined by using the tight gas well dynamic analysis method; Based on the final recoverable reserves and dynamic reserves of each well under the existing well pattern of the tight gas reservoir, the sublayer dynamic reserves of each development layer series in the well pattern adjustment area are determined by using the productivity splitting method.

5. The method according to any one of claims 1 to 4, characterized in that, The well spacing variation coefficient of each development layer series in the well pattern adjustment area is determined based on the coordinates of the existing gas wells in the well pattern adjustment area and the development layer series corresponding to the gas wells, and includes: The coordinates of all gas wells in the well pattern adjustment area are counted, and the development layer series of each gas well is determined through perforation data; Based on the coordinates of the gas wells and the development layer series corresponding to the gas wells, the well spacing of the well pattern in each development layer series in the well pattern adjustment area is determined; Based on the well spacing of the well pattern in each development layer series in the well pattern adjustment area, the mean value and the standard deviation of the well spacing in each development layer series in the well pattern adjustment area are determined; Based on the mean value and the standard deviation of the well spacing in each development layer series in the well pattern adjustment area, the well spacing variation coefficient of each development layer series in the well pattern adjustment area is determined.

6. A method of compact gas reservoir well pattern design, characterized by, It comprises: The well pattern of the gas well designed by the optimization adjustment scheme of the tight gas reservoir well pattern adjustment optimization method according to any one of claims 1-5.

7. A device for optimizing well pattern adjustment in a tight gas reservoir, characterized in that, It comprises: A static reserve determination module for determining the sublayer static reserves of each development layer series in the well pattern adjustment area based on the reservoir parameters of the well pattern adjustment area of the tight gas reservoir; A dynamic reserve determination module for determining the sublayer dynamic reserves of each development layer series in the well pattern adjustment area based on the current development conditions of the well pattern adjustment area of the tight gas reservoir; A dynamic-static reserve ratio and concentration degree determination module for determining the sublayer dynamic-static reserve ratio and the unproduced reserve concentration degree of each development layer series in the well pattern adjustment area based on the sublayer static reserves and the sublayer dynamic reserves of each development layer series in the well pattern adjustment area; A variation coefficient determination module for determining the well spacing variation coefficient of each development layer series in the well pattern adjustment area based on the coordinates of the existing gas wells in the well pattern adjustment area and the development layer series corresponding to the gas wells; An optimization adjustment module for optimizing and adjusting the well pattern of the tight gas reservoir based on the sublayer dynamic-static reserve ratio, the unproduced reserve concentration degree and the well spacing variation coefficient of each development layer series in the well pattern adjustment area.

8. A compact gas reservoir well pattern design apparatus, characterized by, It comprises: The well pattern of the gas well designed by the optimization adjustment scheme of the tight gas reservoir well pattern adjustment optimization method according to any one of claims 1-5.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the tight gas reservoir well pattern adjustment optimization method according to any one of claims 1-5, or to implement the tight gas reservoir well pattern design method according to claim 6.

10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that, The program is executed by the processor to implement the tight gas reservoir well pattern adjustment optimization method according to any one of claims 1-5, or to implement the tight gas reservoir well pattern design method according to claim 6.

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