Method and device for optimizing intermittent well shut-in time of compact gas reservoir

Abstract

The application discloses a method and device for optimizing shut-in time of intermittent well in compact gas reservoir, wherein the method comprises the following steps: obtaining casing pressure data after shut-in and corresponding shut-in time; obtaining the change trend of the shut-in time and determining casing pressure recovery rate threshold according to casing pressure data, the change trend and gas well pressure stabilization standard; performing curve fitting operation on the casing pressure data and the shut-in time to establish a pressure drop rate model; and obtaining the optimized shut-in time according to the pressure drop rate model, fitting curve parameters and the casing pressure recovery rate threshold. The application has strong reliability by collecting real-time gas well production data, which reflects the influence of wellbore fluid accumulation and pipeline freezing blocking on gas well production in the actual production process of intermittent gas well in compact gas reservoir, thereby improving the production efficiency of intermittent gas well in compact gas reservoir and fully exerting the production capacity of intermittent gas well.

Description

Technical Field

[0001] This invention relates to the field of gas field development technology, and in particular to a method and apparatus for optimizing the shut-in time of intermittent wells in tight gas reservoirs, applicable to determining the shut-in time of intermittent wells in tight gas reservoirs in the Ordos Basin. Background Technology

[0002] Tight gas reserves are abundant both domestically and internationally. However, in low-permeability reservoirs, due to the special nature of the pore structure, the flow of fluid through the pore medium is subject to significant resistance, resulting in low fluid flow efficiency and thus affecting the permeability of the low-permeability reservoir.

[0003] During production, gas wells in tight gas reservoirs with low permeability often experience low production and rapid decline. These problems are frequently related to the low permeability, low porosity, and low pressure of tight gas reservoirs. Field practice shows that to maintain production, approximately 40% of production time and 30% of output need to be achieved through intermittent well shut-in / out. Therefore, optimizing the shut-in time is crucial for improving the production efficiency and overall utilization efficiency of gas wells. By rationally setting the shut-in time, the production capacity of gas wells can be maximized, thereby improving well utilization efficiency.

[0004] Currently, well shut-in time optimization is mainly divided into two categories: theoretical analysis and empirical statistical methods. Theoretical analysis typically relies on numerical simulation software (such as Eclipse) or production decline analysis software (such as RTA). Using these software programs, based on fitting historical gas well production data, different shut-in time schemes are set to predict the natural gas production and cumulative production (i.e., the total amount of natural gas produced by the well from the start of production to a specific time point) after well shut-in. The optimal shut-in time is selected by comparing the cumulative production under different shut-in time schemes. However, this method often fails to fully consider the impact of actual conditions such as wellbore fluid accumulation and pipeline freezing on gas well pressure recovery, thus limiting its practical application and leading to poor well reliability. Empirical statistical methods, on the other hand, focus on field tests and practical operational experience. By implementing different shut-in time schemes in the field, observing the production effects of the gas well, and conducting comparative analysis, a better shut-in time can be selected. Although this method is more in line with actual production conditions and takes into account the actual production characteristics of gas wells in a short period of time, it requires a long evaluation period to assess the effectiveness of different schemes and is difficult to adapt to the impact of changes in formation energy, process measures and liquid accumulation conditions.

[0005] In summary, the commonly used methods for optimizing the shut-in time of intermittent gas wells have problems such as poor reliability and outdated understanding, making it difficult to meet the actual production needs of natural gas.

[0006] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section. Summary of the Invention

[0007] This invention provides a method for optimizing the shut-in time of intermittent wells in tight gas reservoirs, in order to improve the production efficiency of intermittent gas wells in tight gas reservoirs and fully utilize the production capacity of intermittent gas wells.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0009] In a first aspect, the present invention provides a method for optimizing the shut-in time of intermittent wells in tight gas reservoirs, comprising:

[0010] Acquire the casing pressure data after well shut-in and the corresponding well shut-in time;

[0011] The trend of the shut-in time is obtained and the casing pressure recovery rate threshold is determined based on the casing pressure data, the trend, and the gas well pressure stability standard.

[0012] The casing pressure data and the shut-in time are subjected to curve fitting to establish a pressure drop rate model.

[0013] Based on the pressure drop rate model, the fitting curve parameters, and the casing pressure recovery rate threshold, the optimized shut-in time is obtained.

[0014] Furthermore, before determining the casing pressure recovery rate threshold based on the casing pressure data, the changing trend, and the gas well pressure stability standard, the method further includes: determining the changing trend of the casing pressure data and the shut-in time based on natural gas production parameters and reservoir parameters; wherein, the natural gas production parameters include natural gas production, natural gas viscosity, and production time before shut-in, and the reservoir parameters include formation pore pressure, reservoir permeability, and effective reservoir thickness.

[0015] Furthermore, the step of performing curve fitting operation on the casing pressure data and the shut-in time to establish a pressure drop rate model includes: performing curve fitting operation on the casing pressure data and the shut-in time to obtain a casing pressure-shut-in time relationship model and fitting curve parameters; and generating the pressure drop rate model based on the casing pressure-shut-in time relationship model and fitting curve parameters.

[0016] Further, generating the pressure drop rate model based on the casing pressure and shut-in time relationship model and the fitting curve parameters includes: determining t based on the casing pressure and shut-in time relationship model. s The pressure at time and t s +1 time period pressure; where t s Let t be the shut-in time. sThe range of values ​​for is positive integers greater than or equal to zero; according to t s The pressure at time t s A pressure drop rate model is established based on the casing pressure at time +1 and the parameters of the fitted curve.

[0017] Secondly, embodiments of the present invention also provide a shut-in time optimization device for intermittent gas wells in tight gas reservoirs, used to improve the production efficiency of intermittent gas wells in tight gas reservoirs and fully utilize the production capacity of intermittent gas wells. The shut-in time optimization device includes:

[0018] The data acquisition module is used to acquire the casing pressure data after well shut-in and the well shut-in time corresponding to the casing pressure data;

[0019] The casing pressure recovery rate threshold determination module is used to acquire the changing trend of the shut-in time and determine the casing pressure recovery rate threshold based on the casing pressure data, the changing trend and the gas well pressure stability standard.

[0020] The curve fitting module is used to perform curve fitting operations on the casing pressure data and the shut-in time to establish a pressure drop rate model.

[0021] The shut-in time optimization module is used to obtain the optimized shut-in time based on the pressure drop rate model, the fitting curve parameters, and the casing pressure recovery rate threshold.

[0022] Furthermore, the shut-in time optimization device also includes a trend determination module, specifically used to determine the trend of the casing pressure data and shut-in time based on natural gas production parameters and reservoir parameters; wherein, the natural gas production parameters include: natural gas production, natural gas viscosity and production time before shut-in, and the reservoir parameters include: formation pore pressure, reservoir permeability and effective reservoir thickness.

[0023] Furthermore, the curve fitting module includes:

[0024] The curve fitting unit is used to perform curve fitting operations on the casing pressure data and the shut-in time to obtain the relationship model between casing pressure and shut-in time and the fitting curve parameters.

[0025] The model building unit is used to generate the pressure drop rate model based on the casing pressure and shut-in time relationship model and fitting curve parameters.

[0026] Furthermore, the model building unit includes:

[0027] The casing pressure determination subunit is used to determine t based on the casing pressure and shut-in time relationship model. s The pressure at time and t s +1 time period pressure; where t s Let t be the shut-in time. sThe range of values ​​for is positive integers greater than or equal to zero;

[0028] The pressure drop rate model establishes sub-units for use based on t s The pressure at time t s A pressure drop rate model is established based on the casing pressure at time +1 and the parameters of the fitted curve.

[0029] This 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 computer program, it implements the above-mentioned method for optimizing the shut-in time of intermittent wells in tight gas reservoirs.

[0030] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for optimizing the shut-in time of intermittent wells in tight gas reservoirs.

[0031] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for optimizing the shut-in time of intermittent wells in tight gas reservoirs.

[0032] This invention provides a method and apparatus for optimizing the shut-in time of intermittent wells in tight gas reservoirs. By collecting gas well production data in real time, the method reflects the impact of wellbore fluid accumulation and pipeline freezing on gas well production during actual production. Because the gas well production data is accurate and reliable, it allows for timely determination of the optimal shut-in time for each intermittent gas well during each intermittent cycle, maximizing the well's production capacity. In actual production, field practice in a gas field shows that optimizing the shut-in time of intermittent gas wells increases the average daily gas production by 14% during the intermittent cycle. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0034] Figure 1 This is a flowchart illustrating a method for optimizing the shut-in time of intermittent wells in tight gas reservoirs according to an embodiment of the present invention.

[0035] Figure 2This is a flowchart illustrating the method for optimizing the shut-in time of intermittent wells in tight gas reservoirs in another embodiment of the present invention.

[0036] Figure 3 This is a flowchart illustrating the method for optimizing the shut-in time of intermittent wells in tight gas reservoirs in another embodiment of the present invention.

[0037] Figure 4 This is a graph showing the relationship between casing pressure and shut-in time in intermittent gas well A according to an embodiment of the present invention.

[0038] Figure 5 This is a schematic diagram of the structure of a tight gas reservoir intermittent well shut-in time optimization device in one embodiment of the present invention;

[0039] Figure 6 This is a schematic diagram of the shut-in time optimization device for intermittent wells in tight gas reservoirs in another embodiment of the present invention;

[0040] Figure 7 This is a schematic diagram of the shut-in time optimization device for intermittent wells in tight gas reservoirs in another embodiment of the present invention;

[0041] Figure 8 This is a schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0043] The information collected in the technical solution of this application is information and data authorized by the user or fully authorized by all parties. The collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant countries and regions, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation portals are provided for users to choose to authorize or refuse.

[0044] The acquisition, transmission, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0045] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0046] In order to improve the production efficiency of intermittent gas wells in tight gas reservoirs and fully utilize their production capacity, this invention provides a method for optimizing the shut-in time of intermittent gas wells in tight gas reservoirs. The main body for implementing this method is [missing information].

[0047] Figure 1 This is a flowchart illustrating a method for optimizing shut-in time in intermittent wells of tight gas reservoirs according to an embodiment of the present invention. Figure 1 As shown, it includes steps 101 to 104.

[0048] Step 101: Obtain the casing pressure data after well shut-in and the corresponding well shut-in time.

[0049] Step 102: Obtain the trend of well shut-in time and determine the casing pressure recovery rate threshold based on casing pressure data, trend, and gas well pressure stability standard.

[0050] Step 103: Perform curve fitting on the casing pressure data and shut-in time to establish a pressure drop rate model.

[0051] Step 104: Based on the pressure drop rate model, fitting curve parameters, and casing pressure recovery rate threshold, obtain the optimized shut-in time.

[0052] from Figure 1 As shown in the flowchart, in this embodiment of the invention, the casing pressure data after well shut-in and the corresponding shut-in time are obtained to analyze the changing trend of casing pressure with shut-in time. The casing pressure recovery rate threshold is determined by analyzing the processed trend and the gas well pressure stability standard. As the shut-in time increases, the corresponding casing pressure recovery rate decreases, and the gas well pressure recovery efficiency decreases. A pressure drop rate model is established by curve fitting of the casing pressure data and shut-in time. Using the casing pressure recovery rate threshold as the lower limit, the shut-in time corresponding to the casing pressure recovery rate threshold is determined by the pressure drop rate model as the optimized shut-in time, thereby improving the production efficiency of intermittent gas wells in tight gas reservoirs and fully utilizing the production capacity of intermittent gas wells.

[0053] like Figure 1 As shown below, taking well A of an intermittent gas well in a gas field as an example, each step will be explained in detail.

[0054] Step 101: Obtain the casing pressure data after well shut-in and the corresponding well shut-in time.

[0055] Specifically, the casing pressure data after well shut-in and the corresponding shut-in time are monitored in real time to obtain the real-time casing pressure test data table for the gas well shut-in, as shown in the table below.

[0056]

[0057] Real-time casing pressure test data table for well shut-in

[0058] Theoretical research on gas well pressure recovery and actual gas well production practice show that the casing pressure after shut-in has a logarithmic relationship with the shut-in time. Meanwhile, the casing pressure recovery rate exhibits a certain variation pattern with the shut-in time; that is, as the shut-in time increases, the casing pressure recovery rate decreases, and the gas well pressure recovery efficiency declines.

[0059] In one embodiment, before determining the casing pressure recovery rate threshold based on casing pressure data, trends, and gas well pressure stability standards, the trends in casing pressure and shut-in time are first determined based on natural gas production parameters and reservoir parameters. The natural gas production parameters include natural gas production rate q. cs Natural gas viscosity μ gi Production time t before well shut-in p and natural gas volume factor B gi etc.; reservoir parameters include formation pore pressure p R The reservoir permeability k, the effective reservoir thickness h, and the unit conversion factor A.

[0060] Specifically, Formula 1 is used to determine the changing trends of casing pressure and shut-in time after well shut-in.

[0061] Formula 1:

[0062] Among them, P R Formation pore pressure, i.e., formation pressure, is expressed in MPa; A is a unit conversion factor; q cs Natural gas production, in cubic meters (m³). 3 / d;B gi μ is the natural gas volume factor. gi t represents the viscosity of natural gas, in cp; k represents the reservoir permeability, in mD; h represents the effective thickness of the reservoir, in m; p Production time before well shut-in, in hours; P ws Casing pressure, also known as casing pressure, is used to describe the variation characteristics of formation energy, and its unit is MPa; t s This refers to the well shut-in time, expressed in hours (h).

[0063] As shown in Formula 1, the bottom casing pressure P after shutting in an intermittent gas well is... ws With shut-in time t s There is a nearly logarithmic relationship, which increases with the shut-in time t. s Increase, wellbore casing pressure P ws The pressure increases accordingly, while the increase in wellhead casing pressure decreases. Therefore, according to Formula 1, it can be deduced that the pressure increases with shut-in time t. s As the pressure increases, the casing pressure recovery rate of intermittent gas wells decreases, thereby reducing the gas well pressure recovery efficiency.

[0064] In one embodiment, based on seepage theory and the above formula, it can be concluded that the casing pressure increases with the extension of the well shut-in time. Since the change in casing pressure reflects the change in formation pressure, the change in formation energy can be inferred. Therefore, the longer the well shut-in time, the higher the casing pressure, indicating a higher degree of formation energy recovery and a stronger fluid-carrying production capacity of the gas well, thus providing a theoretical basis for rationally optimizing the shut-in time.

[0065] Step 102: Obtain the trend of well shut-in time and determine the casing pressure recovery rate threshold based on casing pressure data, trend, and gas well pressure stability standard.

[0066] Specifically, the casing pressure recovery rate threshold is calculated based on the casing pressure data in the real-time casing pressure test data table, the changing trends of the casing pressure and shut-in time, and the gas well pressure stability standard.

[0067] According to the relevant provisions in the "SY / T5440-2019 Technical Specification for Natural Gas Well Testing", a casing pressure recovery of less than 0.5% within 8 hours is taken as the standard for gas well pressure stability. Since the casing pressure of intermittent gas wells in tight gas reservoirs is generally 3-4 MPa during the intermittent phase, 3.5 MPa is taken as the casing pressure during the intermittent phase.

[0068] Therefore, the formula for calculating the casing pressure recovery rate is 3.5 × 0.5% ÷ 8 = 0.002 MPa / h, that is, the threshold value for the casing pressure recovery rate is 0.002 MPa / h.

[0069] In this embodiment of the invention, the optimal value of the casing pressure recovery rate threshold is determined by analyzing the obtained casing pressure data after shut-in and the corresponding shut-in time variation trend, based on the casing pressure data, variation trend, and gas well pressure stability standard. Since casing pressure can reflect formation energy variation characteristics and casing pressure data is easy to acquire, using casing pressure as the main control parameter for optimizing shut-in time provides the necessary conditions for the application of the shut-in time optimization scheme, and determines a shut-in time optimization scheme with the casing pressure recovery rate threshold as the optimization objective.

[0070] Step 103: Perform curve fitting on the casing pressure data and shut-in time to establish a pressure drop rate model.

[0071] Specifically, based on the casing pressure data after shutting in the intermittent gas well, as shown in the real-time casing pressure test data table, curve fitting is performed on these casing pressure data and their corresponding shut-in times to establish the casing pressure P after shutting in the intermittent gas well. ws With shut-in time t s The mathematical relationship model.

[0072] In one embodiment, such as Figure 2 As shown, step 103 includes steps 201 and 202.

[0073] Step 201: Perform curve fitting on the casing pressure data and shut-in time to obtain the casing pressure P. ws With shut-in time t s Relationship model and fitting curve parameters. Among them, the casing pressure P... ws With shut-in time t s The relationship model is a semi-logarithmic model, and the parameters of the fitted curve include the slope A and the intercept B of the semi-logarithmic model.

[0074] In one embodiment, casing pressure data is acquired and monitored in real time through a data acquisition system to obtain casing pressure data as shown in the well shut-in real-time casing pressure test data table. This invention does not impose specific limitations on the model of the data acquisition system. The data acquisition system should at least be able to automatically export hourly casing pressure data; in this embodiment, one hour is used as the casing pressure data acquisition time.

[0075] Download the casing pressure data acquired by the data acquisition system (as shown in the table above) and import it into the curve fitting analysis software, using the shut-in time t as the data. s As the x-axis of the curve relating casing pressure and shut-in time, with casing pressure P... ws A scatter plot was created using the vertical axis of the curve relating casing pressure and shut-in time. Curve fitting was then performed using a correlation curve fitting method to obtain the following results: Figure 4 The curve showing the relationship between casing pressure and shut-in time after shutting in an intermittent gas well represents the model of the relationship between casing pressure and shut-in time.

[0076] Based on the casing pressure data in the real-time casing pressure test data table, a curve fitting was performed to obtain the relationship model between casing pressure and shut-in time after shutting in the intermittent gas well.

[0077] Formula 2: P ws =Aln(t) s )+B.

[0078] Where A is the slope of the semi-logarithmic model curve, with a value of 0.1836; and B is the intercept of the semi-logarithmic model curve, with a value of 3.1084.

[0079] In one embodiment, the curve fitting analysis software can be selected from software such as Excel, Python, and ECharts; this embodiment of the invention does not impose specific limitations. The curve fitting method can be selected from curve fitting methods such as nonlinear fitting, least squares method, and neural networks; this embodiment of the invention also does not impose specific limitations.

[0080] Step 202: Generate a pressure drop rate model based on the relationship model between casing pressure and shut-in time and the parameters of the fitted curve.

[0081] In one embodiment, such as Figure 3As shown, step 202 includes steps 301 and 302.

[0082] Step 301: Determine t based on the relationship model between casing pressure and shut-in time. s The pressure P at any moment wsi and t s The sleeve pressure P at time +1 wsi+1 ; where t s For the well shut-in time, t s The range of values ​​for t is s Positive integers ≥ 0, where i is a positive integer ≥ 0.

[0083] Specifically, t s The pressure P at any moment wsi For P wsi =Aln(t) s )+B;t s The sleeve pressure P at time +1 wsi+1 For P wsi+1 =Aln(t) s +1)+B.

[0084] Step 302: Based on t s The pressure at time t s A pressure drop rate model was established based on the casing pressure at time +1 and the parameters of the fitted curve. The parameters of the fitted curve include the slope A and the intercept B of the semi-logarithmic model, with A taking the value of 0.1836 and B taking the value of 3.1084.

[0085] Specifically, t is calculated using Formula 2 based on the values ​​of the slope A and intercept B of the semi-logarithmic model curve. s The pressure P at any moment wsi That is, P wsi =0.1836ln(t) s )+3.1084.

[0086] Then, based on the values ​​of the slope A and intercept B of the semi-logarithmic model curve, t is calculated using Formula 2. s The sleeve pressure P at time +1 esi+1 That is, P wsi+1 =0.1836ln(t) s +1)+3.1084.

[0087] A pressure drop rate model is established based on the formula for the increase in casing pressure per unit time (i.e., Formula 3).

[0088] Formula 3: ΔP ws =P wsi+1 -P wsi .

[0089] Where the unit time is 1 hour, ΔP ws P is the casing pressure recovery rate. wsi+1 For t s The casing pressure at time +1, P wsi For t a The pressure at any given moment.

[0090] According to t a The pressure at time and t s At time +1, the casing pressure increment ΔP is calculated using formula 3. ws That is, Formula 4.

[0091] Formula 4: ΔP ws =[0.1836ln(t)] s +1)+3.1084]-[0.1836ln(t s )+3.1084].

[0092] Based on the obtained casing pressure increment ΔP ws The shut-in time t is obtained through mathematical transformation using Formula 3. s That is, Formula 5.

[0093] Formula 5:

[0094] Step 104: Based on the pressure drop rate model, fitting curve parameters, and casing pressure recovery rate threshold, obtain the optimized shut-in time.

[0095] Specifically, based on the casing pressure recovery rate threshold ΔP ws The optimized shut-in time t was calculated using Formula 5, along with the fitting curve parameters. s It is 91.3h. Wherein, ΔP ws It is 0.002 MPa / h.

[0096] In this embodiment of the invention, the variation law of casing pressure after well shut-in with shut-in time is analyzed by acquiring casing pressure data and corresponding shut-in time data, revealing a semi-logarithmic relationship between casing pressure and shut-in time. A casing pressure recovery rate threshold is determined based on this trend and the gas well pressure stability standard. By curve fitting of casing pressure data and shut-in time, a model of the relationship between casing pressure and shut-in time, as well as a pressure drop rate model, are established. The optimal shut-in time corresponding to the casing pressure recovery rate threshold is then obtained through the pressure drop rate model. The shut-in time optimization scheme provided by this invention utilizes real-time production data from intermittent gas wells, thereby avoiding the impact of wellbore fluid accumulation and pipeline freezing on natural gas production during actual intermittent gas well production. The optimal shut-in time for each intermittent gas well cycle is determined to improve the production efficiency of intermittent gas wells in tight gas reservoirs and fully utilize their production capacity. Field application in a gas field shows that by optimizing the shut-in time, the average daily gas production during the intermittent gas well cycle increased by 14%.

[0097] This invention also provides a shut-in time optimization device for intermittent wells in tight gas reservoirs, as described in the following embodiments. Since the principle behind this shut-in time optimization device is similar to the shut-in time optimization method for intermittent wells in tight gas reservoirs, the implementation of this device can refer to the implementation of the shut-in time optimization method for intermittent wells in tight gas reservoirs; repeated details will not be elaborated further.

[0098] Figure 5 This is a schematic diagram of the shut-in time optimization device for intermittent wells in tight gas reservoirs, as described in an embodiment of the present invention. Figure 5 As shown, the shut-in time optimization device 500 includes a data acquisition module 501, a casing pressure recovery rate threshold determination module 502, a curve fitting module 503, and a shut-in time optimization module 504.

[0099] The data acquisition module 501 is used to acquire the casing pressure data after well shut-in and the well shut-in time corresponding to the casing pressure data.

[0100] The casing pressure recovery rate threshold determination module 502 is used to acquire the changing trend of the shut-in time and determine the casing pressure recovery rate threshold based on the casing pressure data, the changing trend and the gas well pressure stability standard.

[0101] The curve fitting module 503 is used to perform curve fitting operations on the casing pressure data and the shut-in time to establish a pressure drop rate model.

[0102] The shut-in time optimization module 504 is used to obtain the optimized shut-in time based on the pressure drop rate model, the fitting curve parameters and the casing pressure recovery rate threshold.

[0103] In one embodiment, the shut-in time optimization device further includes a trend determination module, specifically used to determine the trend of the casing pressure data and the shut-in time based on natural gas production parameters and reservoir parameters. The natural gas production parameters include: natural gas production rate, natural gas viscosity, and production time before shut-in; the reservoir parameters include: formation pore pressure, reservoir permeability, and effective reservoir thickness.

[0104] In one embodiment, such as Figure 6 As shown, the curve fitting module 503 includes a curve fitting unit 601 and a model building unit 602.

[0105] The curve fitting unit 601 is used to perform curve fitting operation on the casing pressure data and the shut-in time to obtain the relationship model between casing pressure and shut-in time and the fitting curve parameters.

[0106] The model building unit 602 is used to generate the pressure drop rate model based on the relationship model between casing pressure and shut-in time and the fitting curve parameters.

[0107] In one embodiment, such as Figure 7 As shown, the above model building unit 602 includes a pressure determination subunit 701 and a pressure drop rate model building subunit 702.

[0108] The casing pressure determination subunit 701 is used to determine t based on the casing pressure and shut-in time relationship model. s The pressure at time and t s +1 time period pressure. Where t s Let t be the shut-in time. s The range of values ​​for is positive integers greater than or equal to zero.

[0109] The pressure drop rate model is established by sub-unit 702, which is used to determine the pressure drop rate based on t. s The pressure at time t s A pressure drop rate model is established based on the casing pressure at time +1 and the parameters of the fitted curve.

[0110] Figure 8 This is a schematic diagram of the physical structure of the computer device 800 provided in an embodiment of the present invention, as shown below. Figure 8 As shown, the computer device 800 includes a processor 801, a memory 802, and a bus 803.

[0111] The processor 801 and the memory 802 communicate with each other via the bus 803.

[0112] The processor 801 is used to call program instructions in the memory 802 to execute the methods provided in the above-described method embodiments.

[0113] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0114] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method.

[0115] 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, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the shut-in time of intermittent wells in tight gas reservoirs, characterized in that, include: Acquire the casing pressure data after well shut-in and the corresponding well shut-in time; The trend of the shut-in time is obtained and the casing pressure recovery rate threshold is determined based on the casing pressure data, the trend, and the gas well pressure stability standard. The casing pressure data and the shut-in time are subjected to curve fitting to establish a pressure drop rate model. Based on the pressure drop rate model, the fitting curve parameters, and the casing pressure recovery rate threshold, the optimized shut-in time is obtained.

2. The method according to claim 1, characterized in that, Before determining the casing pressure recovery rate threshold based on the casing pressure data, the changing trend, and the gas well pressure stability standard, the method further includes: The trend of the casing pressure data and shut-in time is determined based on the natural gas production parameters and reservoir parameters; wherein, the natural gas production parameters include natural gas production, natural gas viscosity and production time before shut-in, and the reservoir parameters include formation pore pressure, reservoir permeability and effective reservoir thickness.

3. The method according to claim 1, characterized in that, The step of performing curve fitting on the casing pressure data and the shut-in time to establish a pressure drop rate model includes: The casing pressure data and the shut-in time are subjected to curve fitting to obtain the relationship model between casing pressure and shut-in time and the fitting curve parameters. The pressure drop rate model is generated based on the relationship model between casing pressure and shut-in time and the parameters of the fitted curve.

4. The method according to claim 3, characterized in that, The step of generating the pressure drop rate model based on the casing pressure and shut-in time relationship model and the fitting curve parameters includes: t is determined based on the aforementioned model relating casing pressure and shut-in time. s The pressure at time and t s +1 time period pressure; where t s Let t be the shut-in time. s The range of values ​​for is positive integers greater than or equal to zero; According to t s The pressure at time t s A pressure drop rate model is established based on the casing pressure at time +1 and the parameters of the fitted curve.

5. A device for optimizing shut-in time of intermittent wells in tight gas reservoirs, characterized in that, include: The data acquisition module is used to acquire the casing pressure data after well shut-in and the well shut-in time corresponding to the casing pressure data; The casing pressure recovery rate threshold determination module is used to acquire the changing trend of the shut-in time and determine the casing pressure recovery rate threshold based on the casing pressure data, the changing trend and the gas well pressure stability standard. The curve fitting module is used to perform curve fitting operations on the casing pressure data and the shut-in time to establish a pressure drop rate model. The shut-in time optimization module is used to obtain the optimized shut-in time based on the pressure drop rate model, the fitting curve parameters, and the casing pressure recovery rate threshold.

6. The apparatus according to claim 5, characterized in that, It also includes a trend determination module, which is specifically used to determine the trend of the casing pressure data and the shut-in time based on natural gas production parameters and reservoir parameters; The natural gas production parameters include: natural gas production, natural gas viscosity, and production time before well shut-in; the reservoir parameters include: formation pore pressure, reservoir permeability, and effective reservoir thickness.

7. The apparatus according to claim 5, characterized in that, The curve fitting module includes: The curve fitting unit is used to perform curve fitting operations on the casing pressure data and the shut-in time to obtain the relationship model between casing pressure and shut-in time and the fitting curve parameters. The model building unit is used to generate the pressure drop rate model based on the casing pressure and shut-in time relationship model and fitting curve parameters.

8. The apparatus according to claim 7, characterized in that, The model building unit includes: The casing pressure determination subunit is used to determine t based on the casing pressure and shut-in time relationship model. s The pressure at time and t s +1 time period pressure; where t s Let t be the shut-in time. s The range of values ​​for is positive integers greater than or equal to zero; The pressure drop rate model establishes sub-units for use based on t s The pressure at time t s A pressure drop rate model is established based on the casing pressure at time +1 and the parameters of the fitted curve.

9. A computer device, 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 method of any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 4.

11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 4.

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