A method and system for predicting the optimal well density and infill drilling timing in tight gas reservoirs.

Abstract

This invention discloses a method and system for predicting the optimal well density and infill drilling timing for tight gas reservoirs. The method includes: determining the optimal well density of the sand body to be predicted based on its logging permeability, reserve abundance, and a pre-established prediction chart for optimal well density in tight gas reservoirs; if the sand body meets the infill drilling conditions, determining the optimal infill drilling timing based on its logging permeability, reserve abundance, and a pre-established prediction chart for infill drilling timing in tight gas reservoirs. This invention can rapidly predict optimal well density and infill drilling timing based on known sand body logging permeability and reserve abundance, and can be widely applied in the exploration and development of tight gas reservoirs.

Description

Technical Field

[0001] This invention relates to the field of tight gas reservoir exploration and development, and in particular to a method and system for predicting the appropriate well density and timing of infill adjustments for tight gas reservoirs. Background Technology

[0002] In recent years, China's oil and gas resources have entered a stage of development that emphasizes both conventional and unconventional methods. Unconventional oil and gas accounts for 41% of the country's cumulative proven oil and gas reserves and 20% of total oil and gas production. Tight gas has become an important component in the replacement of unconventional oil and gas production, and its exploration and development potential is enormous.

[0003] However, due to the characteristics of tight gas reservoirs, such as low permeability, strong heterogeneity, small effective reach, and low reserve utilization, well density is the main factor affecting the recovery rate of tight gas reservoirs. If the well density is too low, the well network will not be able to control the reserves sufficiently due to poor reservoir continuity and strong planar heterogeneity, making it difficult to fully utilize the reserves and resulting in a low final recovery rate. However, if the well density is too high, inter-well interference will become more severe. Although the recovery rate can be further improved, the economic benefits are difficult to guarantee. Moreover, when increasing the well density, the timing of deploying infill wells also directly affects the production enhancement effect.

[0004] Existing technologies and methods are neither economical nor applicable for evaluating the appropriate well density and infill drilling timing for reservoirs with different physical properties in tight gas reservoirs. Therefore, accurately and quickly determining the appropriate well density and infill drilling timing for reservoirs with different physical properties in tight gas reservoirs is of great significance for the economical and effective development of tight gas reservoirs. Summary of the Invention

[0005] To address the aforementioned problems, the purpose of this invention is to provide a predictive method and system capable of accurately and rapidly determining the appropriate well density and infill adjustment timing for sand bodies with different physical properties in tight gas reservoirs.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a method for predicting the appropriate well density and infill drilling timing in tight gas reservoirs, comprising:

[0008] Based on the logging permeability, reserve abundance, and pre-established prediction chart of reasonable well network density for tight gas reservoirs, determine the reasonable well network density of the sand body to be predicted.

[0009] If the sand body to be predicted has the conditions for infilling, the timing of infilling adjustment for the sand body to be predicted is determined based on the well logging permeability, reserve abundance, and the pre-established tight gas reservoir infilling adjustment timing prediction chart.

[0010] In the above-mentioned prediction method for reasonable well network density and infill adjustment timing of tight gas reservoirs, the horizontal axis of the prediction chart for reasonable well network density of tight gas reservoirs is the logging permeability of the sand body to be predicted, and the vertical axis is the reasonable well network density of the sand body to be predicted. Different curves in the chart represent the relationship between logging permeability and reasonable well network density under different reserve abundances.

[0011] Furthermore, the reasonable well pattern density prediction chart for tight gas reservoirs is based on a numerical model, which simulates the relationship between well pattern density and well pattern density evaluation index under different permeabilities and reserve abundances. The reasonable well pattern density under different permeabilities and reserve abundances is determined and established using the well pattern density evaluation index standard.

[0012] Furthermore, the numerical model is established based on the geological characteristic parameters of the Linxing tight sandstone gas reservoir;

[0013] The well network density evaluation indicators include the average single-well production for evaluating the economic benefits of a single well in a tight gas reservoir and the increase in the degree of recovery for evaluating the overall economic benefits.

[0014] The well network density evaluation index standard is established to meet the economic requirements of tight gas reservoir development, namely, the average single well production ≥ the minimum average single well production of ordinary wells, and the recovery degree increment ≥ the recovery degree increment threshold.

[0015] The minimum average single-well production = average single-well comprehensive investment ÷ (gas price - comprehensive operating cost - unit tax);

[0016] The threshold for incremental extraction is calculated as follows: (Reserve abundance ÷ 1.2) × (7.5%).

[0017] The formula for calculating the average comprehensive investment per well is as follows:

[0018] Average total investment per conventional well = drilling and completion costs + surface engineering construction costs;

[0019] The average total investment per infill well equals the drilling and completion costs.

[0020] In the above-mentioned prediction method for reasonable well network density and infill adjustment timing of tight gas reservoirs, when (actual number of sand bodies + 1) ÷ sand body area ≤ predicted reasonable well network density, it means that the sand body to be predicted has the conditions for infill adjustment.

[0021] The horizontal axis of the tight gas reservoir infill adjustment timing prediction chart is the logging permeability of the sand body to be predicted, and the vertical axis is the infill adjustment timing of the sand body to be predicted. Different curves in the chart represent the relationship between logging permeability and infill adjustment timing under different reserve abundances.

[0022] The timing of the adjustment refers to the degree of sand body recovery when deploying infill wells;

[0023] The timing of the encryption adjustment refers to the maximum sand body recovery level that can be deployed in the encryption well;

[0024] If the actual production rate is less than or equal to the predicted timing for infiltration adjustment when deploying infiltration wells in a sand body, then the sand body is currently suitable for deploying infiltration wells. If the actual production rate is greater than the predicted timing for infiltration adjustment when deploying infiltration wells in a sand body, then the sand body is currently unsuitable for deploying infiltration wells.

[0025] Furthermore, the tight gas reservoir infill adjustment timing prediction chart is based on a numerical model, simulating the relationship between adjustment timing and adjustment timing evaluation indicators under different permeability and reserve abundance, and using adjustment timing evaluation indicator standards to determine the infill adjustment timing under different permeability and reserve abundance.

[0026] Furthermore, the numerical model is established based on the geological characteristic parameters of the Linxing tight sandstone gas reservoir;

[0027] The evaluation index for the timing of the adjustment is the cumulative gas production increase of the sand body after the deployment of infill wells in a tight gas reservoir.

[0028] The evaluation criteria for the timing of the adjustment are established to meet the economic requirements of tight gas reservoir development, namely, the cumulative gas production increment of the sand body after the deployment of infill wells is greater than or equal to the minimum average single-well production of the infill wells.

[0029] The minimum average single-well production = average single-well comprehensive investment ÷ (gas price - comprehensive operating cost - unit tax);

[0030] The formula for calculating the average comprehensive investment per well is as follows:

[0031] Average total investment per conventional well = drilling and completion costs + surface engineering construction costs;

[0032] The average total investment per infill well equals the drilling and completion costs.

[0033] Secondly, the present invention provides a system for predicting the reasonable well network density and infill adjustment timing of tight gas reservoirs, comprising:

[0034] The reasonable well pattern density prediction module is used to determine the reasonable well pattern density of the sand body to be predicted based on the logging permeability, reserve abundance and the pre-established reasonable well pattern density prediction chart of tight gas reservoir.

[0035] The infill adjustment timing prediction module is used to determine the infill adjustment timing of the sand body to be predicted based on the well logging permeability, reserve abundance, and a pre-established tight gas reservoir infill adjustment timing prediction chart.

[0036] Thirdly, the present invention provides a processing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the steps corresponding to the tight gas reservoir reasonable well network density and infill adjustment timing prediction method as described in any of the preceding claims.

[0037] Fourthly, the present invention provides a computer-readable storage medium storing computer program instructions, characterized in that, when executed by a processor, the computer program instructions are used to implement the steps corresponding to the method for predicting the reasonable well network density and infill adjustment timing of tight gas reservoirs as described in any of the above claims.

[0038] The present invention has the following advantages due to the adoption of the above technical solutions:

[0039] 1. This invention can rapidly predict well network density based on known sand body permeability and reserve abundance, using a reasonably established well network density prediction chart. Compared with traditional well network density evaluation methods, it significantly improves the prediction speed and avoids prediction deviations caused by inaccurate values ​​in traditional methods, resulting in more realistic, accurate, and reliable results.

[0040] 2. This invention can quickly predict the timing of infill well deployment based on known sand body permeability and reserve abundance, according to the established infill adjustment timing prediction chart. Compared with the traditional method of determining the timing of infill well deployment based on experience, it significantly improves the prediction speed, avoids prediction deviations caused by inaccurate experience, and increases the accuracy of prediction results.

[0041] In summary, this invention can be widely applied in the field of tight gas reservoir exploration and development. Attached Figure Description

[0042] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings:

[0043] Figure 1 This is a schematic diagram of a method flow provided in an embodiment of the present invention;

[0044] Figure 2 This is a prediction chart of reasonable well pattern density for tight gas reservoirs provided in an embodiment of the present invention;

[0045] Figure 3 This is a prediction chart for the timing of tight gas reservoir infilling and adjustment provided in an embodiment of the present invention;

[0046] Figure 4This is a process provided by an embodiment of the present invention for determining a reasonable well pattern density using evaluation index standards in the relationship curve between evaluation index and well pattern density;

[0047] Figure 5 This is a process provided by an embodiment of the present invention for determining the timing of encryption adjustment by using evaluation index standards in the relationship curve between evaluation index and adjustment timing. Detailed Implementation

[0048] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0049] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0050] For tight gas reservoirs, it is difficult to accurately and quickly evaluate the appropriate well density and infill adjustment timing for sand bodies with different physical properties. The present invention provides a method and system for predicting the appropriate well density and infill adjustment timing for tight gas reservoirs. Based on pre-established prediction maps for appropriate well density and infill adjustment timing in tight gas reservoirs, it can accurately and quickly determine the appropriate well density and infill adjustment timing for the sand bodies to be predicted. To illustrate the technical solution described in this invention, specific embodiments are provided below.

[0051] Example 1

[0052] like Figure 1 As shown in the figure, this embodiment provides a method for predicting the reasonable well pattern density and infill drilling timing of tight gas reservoirs. The method may include the following steps:

[0053] 1) Determine the reasonable well network density of the sand body to be predicted based on the logging permeability, reserve abundance, and the pre-established reasonable well network density prediction chart of the tight gas reservoir.

[0054] Specifically, the prediction chart for reasonable well pattern density in tight gas reservoirs is as follows: Figure 2 As shown, the horizontal axis represents the logging permeability of the sand body to be predicted, and the vertical axis represents the reasonable well pattern density of the sand body to be predicted. Different curves in the figure represent the relationship between logging permeability and reasonable well pattern density under different reserve abundances.

[0055] Specifically, when the actual well density of the sand body is less than or equal to the predicted reasonable well density, the sand body production effect is good; when the actual well density of the sand body is greater than or equal to the predicted reasonable well density, the sand body production effect is poor.

[0056] 2) If the sand body to be predicted has the conditions for infill drilling, the timing of infill drilling adjustment for the sand body to be predicted (i.e. the maximum production level that can be achieved by deploying infill wells for the sand body to be predicted) is determined based on the well logging permeability, reserve abundance and the pre-established tight gas reservoir infill drilling adjustment timing prediction chart.

[0057] Specifically, if (actual number of wells in the sand body + 1) ÷ sand body area ≤ predicted reasonable well density, then the sand body has the conditions for densification and can be densified.

[0058] Specifically, the prediction chart for the timing of tight gas reservoir infill adjustments is as follows: Figure 3 As shown, the horizontal axis represents the logging permeability of the sand body to be predicted, and the vertical axis represents the timing of infill adjustment for the sand body to be predicted. Different curves in the figure represent the relationship between logging permeability and infill adjustment timing under different reserve abundances.

[0059] Specifically, if the actual production rate when deploying infill wells in a sand body is less than or equal to the predicted infill adjustment time, it means that the sand body is currently suitable for deploying infill wells, and the production increase effect of the infill wells is good; if the actual production rate when deploying infill wells in a sand body is greater than the predicted infill adjustment time, it means that the sand body is currently not suitable for deploying infill wells.

[0060] In the above embodiments, preferably, in step 1), the reasonable well pattern density prediction chart for tight gas reservoirs is based on a numerical model, which simulates the relationship between well pattern density and well pattern density evaluation index under different permeability and reserve abundance, and uses the evaluation index standard to determine and establish the reasonable well pattern density under different permeability and reserve abundance.

[0061] Specifically, the numerical model is established based on the geological characteristic parameters of the Linxing tight sandstone gas reservoir; specifically, the numerical model uses a PEBI grid to simulate the sand body, with a model size of 1440m × 700m and an area of ​​1km². 2The original formation pressure was 15.0 MPa, the porosity was 11%, the permeability was 0.4 mD-2.0 mD, the gas saturation was 55%, and the reserve abundance was 0.5 × 10⁻⁶. 8 m 3 / km 2 -2.0×10 8 m 3 / km 2 Different well density patterns are simulated by controlling the number of production wells on the model. Under different well density patterns, the production wells are uniformly distributed on the model.

[0062] Specifically, the evaluation indicators include the average well production for evaluating the economic benefits of a single well in a tight gas reservoir and the recovery rate increment for evaluating the overall economic benefits. The standard is established to meet the economic requirements of tight gas reservoir development, namely, the average well production ≥ the minimum average well production of ordinary wells, and the recovery rate increment ≥ the recovery rate increment threshold;

[0063] The minimum average single-well production = average single-well comprehensive investment ÷ (gas price - comprehensive operating cost - unit tax);

[0064] The gas price is 1m 3 The selling price of natural gas, with a comprehensive operating cost per cubic meter extracted. 3 The cost of natural gas, with a unit tax of 1m³ sold. 3 Natural gas is subject to taxation.

[0065] The threshold for incremental extraction is calculated as follows: (Reserve abundance ÷ 1.2) × (7.5%).

[0066] The formula for calculating the average comprehensive investment per well is as follows:

[0067] Average total investment per conventional well = drilling and completion costs + surface engineering construction costs;

[0068] The average total investment per infill well equals the drilling and completion costs.

[0069] Using the above numerical model, the reserve abundance is controlled at 1.2 × 10⁻⁶. 8 m 3 / km 2 With a permeability of 0.4 mD, changing the number of production wells in the model can simulate the final cumulative gas production and recovery rate under different well density.

[0070] In the evaluation index, the average single-well production when the well density is i = the cumulative gas production when the well density is i ÷ the number of producing wells when the well density is i, i = 1, 2, 3, 4...;

[0071] In the evaluation index, the increase in production rate when the well density is i = the production rate when the well density is i - the production rate when the well density is (i-1), where i = 2, 3, 4, 5...;

[0072] Under current gas price conditions and reserve abundance, the calculated minimum average single-well production for ordinary wells is 1600 × 10⁻⁶. 4 m 3 The threshold for incremental recovery is 7.5%; that is, the evaluation standard is an average single-well production of ≥1600×10⁻⁶. 4 m 3 And the increase in extraction rate is ≥7.5%;

[0073] The relationship between the above-mentioned evaluation indicators and well network density is plotted as follows: Figure 4 As shown, the abundance of reserves was determined to be 1.2 × 10⁻⁶ using the evaluation index standard. 8 m 3 / km 2 When the permeability is 0.4 mD, the reasonable well density is 4.1 wells / km². 2 .

[0074] By keeping the reserve abundance constant and changing the permeability, repeating the above process, we can obtain the reasonable well network density corresponding to different permeabilities under the same reserve abundance.

[0075] By changing the reserve abundance and repeating the above process, the appropriate well density corresponding to different permeabilities under different reserve abundances can be obtained.

[0076] The established relationships between different permeabilities, reserve abundance and reasonable well pattern density of sand bodies are shown in Table 1.

[0077] Table 1. Relationship between different permeabilities and reservoir abundance and the optimal well pattern density of sand bodies.

[0078]

[0079] In the above embodiments, preferably, in step 2), the tight gas reservoir infill adjustment timing prediction chart is established based on a numerical model under the condition that the sand body has infill capabilities. This model simulates the relationship between adjustment timing and adjustment timing evaluation indicators under different permeability and reserve abundance, and uses the adjustment timing evaluation indicator standard to determine the relationship between infill adjustment timing under different permeability and reserve abundance.

[0080] Specifically, the timing of the adjustment refers to the degree of sand body recovery when deploying infill wells.

[0081] Specifically, the timing of densification adjustment refers to the maximum sand body recovery level that can be achieved by deploying densification wells.

[0082] Specifically, the numerical model is established based on the geological characteristic parameters of the Linxing tight sandstone gas reservoir; specifically, the numerical model uses a PEBI grid to simulate the sand body, with a model size of 1440m × 700m and an area of ​​1km². 2 The original formation pressure was 15.0 MPa, the porosity was 11%, the permeability was 0.4 mD-2.0 mD, the gas saturation was 55%, and the reserve abundance was 1.2 × 10⁻⁶. 8 m 3 / km 2 -2.0×10 8 m 3 / km 2 Three wells are evenly arranged on the model. The deployment of densification wells is simulated by controlling the opening time of the middle well. The production level of the model when the middle well is opened is the adjustment time.

[0083] Specifically, the timing of the adjustment is evaluated by the cumulative gas production increase of the sand body after the deployment of infill wells in tight gas reservoirs.

[0084] Specifically, the evaluation criteria for adjusting the timing of the adjustment are based on the economic viability of tight gas reservoir development, namely, the cumulative gas production increment of the sand body after deploying infill wells is greater than or equal to the minimum average single-well production of the infill wells.

[0085] The minimum average single-well production = average single-well comprehensive investment ÷ (gas price - comprehensive operating cost - unit tax);

[0086] The gas price is 1m 3 The selling price of natural gas, with a comprehensive operating cost per cubic meter extracted. 3 The cost of natural gas, with a unit tax of 1m³ sold. 3 Natural gas is subject to taxation.

[0087] The formula for calculating the average comprehensive investment per well is as follows:

[0088] Average total investment per conventional well = drilling and completion costs + surface engineering construction costs;

[0089] The average total investment per infill well equals the drilling and completion costs.

[0090] Using the above numerical model, the reserve abundance is controlled at 1.2 × 10⁻⁶. 8 m 3 / km 2 With a permeability of 0.4 mD-1.0 mD (as shown in Table 1, under this reserve abundance, a permeability greater than 1.0 mD does not meet the conditions for infilling), changing the well opening time of intermediate wells can simulate the final cumulative gas production of the model under different adjustment timings.

[0091] Evaluation index: Cumulative gas production increment after deploying infill wells = Final cumulative gas production of the model with infill wells deployed under different adjustment timings - Final cumulative gas production of the model without infill wells deployed;

[0092] Under current gas price conditions, the calculated minimum average single-well production for infill wells is 1100 × 10⁻⁶. 4 m 3 The evaluation criterion is that the cumulative gas production increase of the sand body after the deployment of infill wells is ≥1100×10 4 m 3 ;

[0093] The relationship between the evaluation indicators obtained above and the timing of adjustments is plotted as follows: Figure 5 As shown, the abundance of reserves can be determined to be 1.2 × 10⁻⁶ using the evaluation index standard. 8 m 3 / km 2 At the same time, the timing of encryption adjustments under different penetration rates;

[0094] By changing the abundance of reserves and repeating the above process, we can obtain the timing of densification adjustments corresponding to different penetration rates under different abundance of reserves.

[0095] The established relationships between different permeabilities, reserve abundance, and sand body infill adjustment timing are shown in Table 2.

[0096] Table 2. Relationship between different permeabilities and reservoir abundance and the timing of sand body infilling adjustments

[0097]

[0098] The following detailed embodiments illustrate the method for predicting the reasonable well pattern density of tight gas reservoirs according to the present invention:

[0099] The actual well density of sand body A is 2.9 wells / km. 2 The permeability K is 1.0 mD, and the abundance is 1.05 × 10⁻⁶ mD. 8 m 3 / km 2 The actual well density of sand body B is 3.0 wells / km². 2 The permeability K is 2.0 mD, and the abundance is 1.26 × 10⁻⁶ mD. 8 m 3 / km 2 ;

[0100] Based on the pre-established prediction chart of reasonable well density for tight gas reservoirs, the permeability K of sand body A is 1.0 mD, and the reserve abundance is 1.05 × 10⁻⁶ mD. 8 m 3 / km 2 The reasonable well density was found to be 3.0 wells / km. 2The permeability K of sand body B is 2.0 mD, and its abundance is 1.26 × 10⁻⁶ mD. 8 m 3 / km 2 The reasonable well density was found to be 2.0 wells / km. 2 .

[0101] The actual well density of sand body A is 2.9 wells / km. 2 <Predicted reasonable well density: 3.0 wells / km 2 The well density is within a reasonable range, and the average single-well production of sand body A is 1890 × 10⁻⁶. 4 m 3 It is greater than the minimum average single-well production of ordinary wells, which is 1600×10 4 m 3 Therefore, the production effect is relatively good; the actual well density of sand body B is 3.0 wells / km. 2 >Predicted reasonable well density: 2.0 wells / km 2 The well network density is unreasonable, and the average single-well production of sand body B is 1143×10 4 m 3 It is less than the minimum average single-well production of ordinary wells, which is 1600×10. 4 m 3 Therefore, the production effect is poor. The prediction results are consistent with the actual production results, proving that the method of the present invention has high accuracy and can greatly improve the prediction speed, allowing for the rapid determination of the number of wells to be deployed based on the physical properties of the sand body when formulating the plan.

[0102] The method for predicting the timing of tight gas reservoir infill adjustment according to another specific embodiment of the present invention is described in detail below:

[0103] Sand body C has the conditions for infill drilling (the actual number of wells in the sand body is 1, and the area of ​​the sand body is 0.90 km²). 2 Calculations show that (actual number of sand bodies + 1) ÷ sand body area ≤ predicted reasonable well density. Therefore, sand body C meets the conditions for infill drilling. During actual infill drilling, the recovery rate was 6.8%, the permeability was 1.2 mD, and the reserve abundance was 1.54 × 10⁻⁶. 8 m 3 / km 2 Sand body D has the conditions for infill drilling (the actual number of wells in the sand body is 1, and the area of ​​the sand body is 0.66 km²). 2 Calculations show that (actual number of sand bodies + 1) ÷ sand body area ≤ predicted reasonable well density. Therefore, sand body D meets the conditions for infill drilling. During actual infill drilling, the recovery rate was 34%, the permeability was 1.5 mD, and the reserve abundance was 1.42 × 10⁻⁶. 8 m 3 / km 2 ;

[0104] Based on the pre-established prediction chart for the timing of tight gas reservoir infill adjustments, the permeability of sand body C is 1.2 mD, and the reserve abundance is 1.54 × 10⁻⁶. 8 m 3 / km 2 The timing for the encryption adjustment was found to be 30%; the permeability K of sand body D was 1.5 mD, and the abundance was 1.42 × 10⁻⁶ m⁻¹. 8 m 3 / km 2 The encryption adjustment timing was found to be 24%.

[0105] The actual adjustment window for sand body C is 6.8% < the predicted infill adjustment window of 30%. Infill wells should be deployed within the recommended adjustment window, and the cumulative gas production increase after deploying infill wells in sand body C will be 1300 × 10⁻⁶. 4 m 3 Greater than the minimum average single-well production of infill wells, 1100×10 4 m 3 Therefore, the infill well production effect is better; the actual adjustment opportunity of sand body D is 34% > the predicted infill adjustment opportunity is 24%, so infill wells are deployed outside the recommended infill adjustment opportunity, and the cumulative gas production increase after the deployment of infill wells in sand body D is 650×10 4 m 3 Less than the minimum average single-well production of infill wells, 1100×10 4 m 3 Therefore, the production effect of infill wells is poor. The prediction results are consistent with the actual production results, proving that the method of the present invention has high accuracy and can greatly improve the prediction speed. It can quickly determine the timing of infill adjustment based on the physical properties of the sand body when deploying infill wells.

[0106] Example 2

[0107] This embodiment provides a prediction system for the reasonable well pattern density and infill adjustment timing of tight gas reservoirs, including:

[0108] The reasonable well density prediction module is used to determine the reasonable well density of the sand body to be predicted based on the physical properties of the sand body to be predicted and the pre-established reasonable well density prediction map of tight gas reservoirs.

[0109] The infill adjustment timing prediction module is used to determine the infill adjustment timing of the sand body to be predicted based on the physical properties of the sand body to be predicted and the pre-established tight gas reservoir infill adjustment timing prediction chart.

[0110] The system provided in this embodiment is used to execute the above-described method embodiments. For specific processes and details, please refer to the above embodiments, which will not be repeated here.

[0111] The system provided in this embodiment can be a software unit, a hardware unit, or a combination of software and hardware built into an existing terminal device. It can also be integrated into the terminal device as an independent component, or it can exist as an independent terminal device.

[0112] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0113] Example 3

[0114] This embodiment provides a processing device corresponding to the tight gas well production capacity prediction method provided in Embodiment 1. The processing device can be a client-side processing device, such as a mobile phone, laptop, tablet computer, desktop computer, etc., to execute the method of Embodiment 1.

[0115] The processing device includes a processor, a memory, a communication interface, and a bus. The processor, memory, and communication interface are connected via the bus to enable communication between them. The memory stores a computer program that can run on the processing device. When the processing device runs the computer program, it executes the steps in the tight gas well production capacity prediction method provided in Embodiment 1.

[0116] In some implementations, the memory may be high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device.

[0117] In other implementations, the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc., without limitation.

[0118] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0119] Those skilled in the art will understand that the structure of the above-described computing device is only a partial structure related to the solution of this application and does not constitute a limitation on the computing device to which the solution of this application is applied. A specific computing device may include more or fewer components, or combine certain components, or have different component arrangements.

[0120] Example 4

[0121] This embodiment provides a computer program product corresponding to the tight gas well production capacity prediction method provided in Embodiment 1. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing the tight gas well production capacity prediction method described in Embodiment 1 are loaded.

[0122] A computer-readable storage medium can be a tangible device that holds and stores instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0123] The computer-readable storage medium provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0124] 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 this application. 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.

[0125] 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.

[0126] 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.

[0127] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for predicting the optimal well density and infill drilling timing in tight gas reservoirs, characterized in that, include: Based on the logging permeability, reserve abundance, and pre-established prediction chart of reasonable well network density for tight gas reservoirs, determine the reasonable well network density of the sand body to be predicted. If the sand body to be predicted has the conditions for infilling, the timing of infilling adjustment for the sand body to be predicted is determined based on the well logging permeability, reserve abundance and the pre-established tight gas reservoir infilling adjustment timing prediction chart. The horizontal axis of the prediction chart for the reasonable well pattern density of the tight gas reservoir is the logging permeability of the sand body to be predicted, and the vertical axis is the reasonable well pattern density of the sand body to be predicted. Different curves in the chart represent the relationship between logging permeability and reasonable well pattern density under different reserve abundances. The reasonable well pattern density prediction chart for tight gas reservoirs is based on a numerical model, which simulates the relationship between well pattern density and well pattern density evaluation index under different permeability and reserve abundance. The reasonable well pattern density under different permeability and reserve abundance is determined and established using the well pattern density evaluation index standard. The numerical model is based on the geological characteristic parameters of the Linxing tight sandstone gas reservoir; The well network density evaluation indicators include the average single-well production for evaluating the economic benefits of a single well in a tight gas reservoir and the increase in the degree of recovery for evaluating the overall economic benefits. The well network density evaluation index standard is established to meet the economic requirements of tight gas reservoir development, namely, the average single well production ≥ the minimum average single well production of ordinary wells, and the recovery degree increment ≥ the recovery degree increment threshold. The minimum average single-well production = average single-well comprehensive investment ÷ (gas price - comprehensive operating cost - unit tax). The threshold for incremental extraction is calculated as follows: (Reserve abundance ÷ 1.2) × (7.5%). The formula for calculating the average comprehensive investment per well is as follows: Average total investment per conventional well = drilling and completion costs + surface engineering construction costs; The average total investment per infill well equals the drilling and completion costs.

2. The method for predicting the reasonable well pattern density and infill adjustment timing of tight gas reservoirs according to claim 1, characterized in that: If (actual number of wells in the sand body + 1) ÷ sand body area ≤ predicted reasonable well density, then the sand body to be predicted has the conditions for densification. The horizontal axis of the tight gas reservoir infill adjustment timing prediction chart is the logging permeability of the sand body to be predicted, and the vertical axis is the infill adjustment timing of the sand body to be predicted. Different curves in the chart represent the relationship between logging permeability and infill adjustment timing under different reserve abundances. The timing of the adjustment refers to the degree of sand body recovery when deploying infill wells; The timing of the encryption adjustment refers to the maximum sand body recovery level that can be deployed in the encryption well; If the actual production rate is less than or equal to the predicted timing for infiltration adjustment when deploying infiltration wells in a sand body, then the sand body is currently suitable for deploying infiltration wells. If the actual production rate is greater than the predicted timing for infiltration adjustment when deploying infiltration wells in a sand body, then the sand body is currently unsuitable for deploying infiltration wells.

3. The method for predicting the reasonable well pattern density and infill adjustment timing of tight gas reservoirs according to claim 1 or 2, characterized in that: The tight gas reservoir infill adjustment timing prediction chart is based on a numerical model, simulating the relationship between adjustment timing and adjustment timing evaluation indicators under different permeability and reserve abundance. The adjustment timing is determined and established using the adjustment timing evaluation indicator standard under different permeability and reserve abundance.

4. The method for predicting the reasonable well pattern density and infill adjustment timing of tight gas reservoirs according to claim 3, characterized in that: The numerical model is based on the geological characteristic parameters of the Linxing tight sandstone gas reservoir; The evaluation index for the timing of the adjustment is the cumulative gas production increment of the sand body after the deployment of infill wells in a tight gas reservoir. The evaluation criteria for the timing of the adjustment are established to meet the economic requirements of tight gas reservoir development, namely, the cumulative gas production increment of the sand body after the deployment of infill wells is greater than or equal to the minimum average single-well production of the infill wells. The minimum average single-well production = average single-well comprehensive investment ÷ (gas price - comprehensive operating cost - unit tax). The formula for calculating the average comprehensive investment per well is as follows: Average total investment per conventional well = drilling and completion costs + surface engineering construction costs; The average total investment per infill well equals the drilling and completion costs.

5. A system for predicting the optimal well density and infill drilling timing in tight gas reservoirs, characterized in that, include: The reasonable well pattern density prediction module is used to determine the reasonable well pattern density of the sand body to be predicted based on the logging permeability, reserve abundance and the pre-established reasonable well pattern density prediction chart of tight gas reservoir. The infill adjustment timing prediction module is used to determine the infill adjustment timing of the sand body to be predicted based on the well logging permeability, reserve abundance, and a pre-established tight gas reservoir infill adjustment timing prediction chart.

6. A processing apparatus, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps corresponding to the method for predicting the reasonable well network density and infill adjustment timing of tight gas reservoirs as described in any one of claims 1-4.

7. A computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they are used to implement the steps corresponding to the method for predicting the reasonable well network density and infill adjustment timing of tight gas reservoirs as described in any one of claims 1-4.

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