Method and device for calculating formation pressure of abnormal high-pressure tight gas well

Abstract

The invention relates to the technical field of abnormal high-pressure formation pressure calculation, in particular to an abnormal high-pressure tight gas well formation pressure calculation method and device. The method comprises the following steps: acquiring gas well data of a target gas well in an abnormal high-pressure state, and calculating first formation pressure; calculating a real-time compression factor based on the gas well data and the first formation pressure; calculating a second formation pressure based on the real-time compression factor and the first formation pressure; and performing iterative optimization on the second formation pressure according to the first formation pressure and a preset comparison threshold value to obtain target formation pressure. According to the embodiment of the invention, the calculation precision of the formation pressure of the abnormal high-pressure gas well can be greatly improved.

Description

Technical Field

[0001] This disclosure relates to the field of abnormally high pressure formation pressure calculation technology, and in particular to a method and apparatus for calculating abnormally high pressure tight gas well formation pressure. Background Technology

[0002] Formation pressure is the soul of oil and gas field development. Obtaining accurate formation pressure provides crucial information for adjusting reservoir plans, evaluating well potential, and selecting post-well drainage and gas production technologies. Currently, commonly used methods for evaluating formation pressure include wellhead pressure reduction, fluid balance, pressure drop curves, and pressure recovery test interpretation. Among these, pressure recovery test interpretation boasts the highest accuracy. The Xinchang Shaximiao Formation gas reservoir in western Sichuan is a typical abnormally high-pressure, low-porosity, and tight gas reservoir. Pressure recovery testing presents the following prominent problems: First, the tight reservoir has low permeability, making it difficult to achieve stable pressure recovery even after prolonged well shut-in. This significantly impacts water-producing gas wells, and prolonged shut-in can easily lead to bottomhole fluid accumulation, increasing maintenance difficulty upon reopening the well and potentially rendering it unusable for production after testing. Second, limited by operating costs and production pressure, pressure recovery testing cannot be carried out on a large scale. Furthermore, some gas well pressure gauges are located at the wellhead, making them highly susceptible to interference from environmental weather and human factors, resulting in abnormal fluctuations in pressure recovery data, poor data quality, and even data that is uninterpretable. Due to the abnormally high pressure characteristics of gas reservoirs, conventional wellhead calculations, fluid balance, and pressure drop methods have low accuracy when compared with measured pressure recovery data. Summary of the Invention

[0003] In view of this, the present disclosure provides a method, apparatus, electronic device and computer-readable storage medium for calculating formation pressure in abnormally high-pressure tight gas wells, in order to solve the problem of low accuracy of calculation methods in the prior art.

[0004] A first aspect of this disclosure provides a method for calculating formation pressure in abnormally high-pressure tight gas wells, comprising:

[0005] Obtain gas well data for the target gas well under abnormal high pressure conditions and calculate the first formation pressure;

[0006] Calculate the real-time compressibility factor based on the gas well data and the first formation pressure;

[0007] The second formation pressure is calculated based on the real-time compressibility factor and the first formation pressure.

[0008] Based on the first formation pressure and a preset comparison threshold, the second formation pressure is iteratively optimized to obtain the target formation pressure.

[0009] In some optional implementations of certain embodiments, calculating the second formation pressure based on the real-time compressibility factor and the first formation pressure includes:

[0010] The combined water-rock compressibility coefficient is calculated based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data.

[0011] The second formation pressure is calculated based on the preset first calculation formula, the real-time compressibility factor, the water-rock composite compressibility coefficient, and the initial compressibility factor, dynamic reserves, and cumulative production in the gas well data. The first calculation formula includes:

[0012]

[0013] Where, p r The real-time formation pressure represented by C e p represents the combined compressibility coefficient of water and rock. i Z represents the initial formation pressure, and Z represents the real-time compressibility factor. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This indicates the real-time cumulative output.

[0014] In some optional implementations of certain embodiments, the calculation of the combined water-rock compressibility coefficient based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data includes:

[0015] Based on the preset second calculation formula, and the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data, the water-rock composite compressibility coefficient is calculated, wherein the second calculation formula includes:

[0016]

[0017] Among them, C e C represents the combined compressibility coefficient of water and rock. f C represents the rock compressibility coefficient. w S represents the compressibility coefficient of bound water. wi This indicates the degree of bound water saturation.

[0018] In some optional implementations of some embodiments, the step of calculating the first formation pressure includes:

[0019] The initial formation pressure, initial compressibility factor, dynamic reserves, and cumulative production from the gas well data are obtained, and the first formation pressure is calculated based on a preset third calculation formula, wherein the third calculation formula includes:

[0020]

[0021] in, p represents the first formation pressure. i Z represents the initial formation pressure. i G represents the initial compressibility factor, and G represents the dynamic reserves.p This indicates the real-time cumulative output.

[0022] In some optional implementations of certain embodiments, calculating the real-time compressibility factor based on the gas well data and the first formation pressure includes:

[0023] Obtain the reservoir temperature, as well as the mole fraction, critical pressure, and critical temperature of each component alkane from the target gas well data;

[0024] The simulated comparative temperature and simulated comparative pressure of the target gas well are calculated based on the first formation pressure, the reservoir temperature, the mole fraction of each component alkane, the critical pressure, and the critical temperature.

[0025] The real-time compression factor is determined based on the proposed comparison temperature and proposed comparison pressure.

[0026] In some optional implementations of certain embodiments, the steps of calculating the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well include:

[0027] According to the preset fourth calculation formula, the reservoir temperature, the mole fraction of each alkane component, the critical pressure and critical temperature, and the first formation pressure are used to calculate the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well, wherein the fourth calculation formula includes:

[0028] p pr =p / ∑y i p ci

[0029] T pr =T / ∑y i T ci

[0030] Where, p pr The pressure to be compared is indicated by p, where p represents the pressure of the first formation, and y represents the pressure of the first formation. i p represents the mole fraction of each individual alkane component. ci T represents the critical pressure of each individual alkane component. pr The relative temperature is T, where T represents the reservoir temperature, and t represents the relative temperature. ci This indicates the critical temperature of each individual alkane component.

[0031] In some optional implementations of certain embodiments, the step of iteratively optimizing the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure includes:

[0032] Calculate the absolute difference between the first and second formation pressures in the previous test.

[0033] If the absolute value difference is greater than the preset judgment threshold, the second formation pressure of the current time is determined as the first formation pressure of the next time, and the step of calculating the real-time compressibility factor based on the gas well data and the first formation pressure is re-executed.

[0034] In some optional implementations of certain embodiments, the method further includes:

[0035] The target formation pressure is imported into the trained fitting model for correction to obtain the corrected formation pressure. The fitting model is trained based on multiple calculated historical formation pressures.

[0036] A second aspect of this disclosure provides an apparatus for calculating formation pressure in abnormally high-pressure tight gas wells, comprising:

[0037] The first calculation module is used to acquire gas well data of the target gas well under abnormal high pressure and calculate the first formation pressure.

[0038] The second calculation module is used to calculate the real-time compressibility factor based on the gas well data and the first formation pressure.

[0039] The third calculation module is used to calculate the second formation pressure based on the real-time compression factor and the first formation pressure;

[0040] The optimization module is used to iteratively optimize the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure.

[0041] In some optional implementations of certain embodiments, calculating the second formation pressure based on the real-time compressibility factor and the first formation pressure includes:

[0042] The combined water-rock compressibility coefficient is calculated based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data.

[0043] The second formation pressure is calculated based on the preset first calculation formula, the real-time compressibility factor, the water-rock composite compressibility coefficient, and the initial compressibility factor, dynamic reserves, and cumulative production in the gas well data. The first calculation formula includes:

[0044]

[0045] Where, p r The real-time formation pressure represented by C e p represents the combined compressibility coefficient of water and rock. i Z represents the initial formation pressure, and Z represents the real-time compressibility factor. i G represents the initial compressibility factor, and G represents the dynamic reserves. pThis indicates the real-time cumulative output.

[0046] In some optional implementations of certain embodiments, the calculation of the combined water-rock compressibility coefficient based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data includes:

[0047] Based on the preset second calculation formula, and the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data, the water-rock composite compressibility coefficient is calculated, wherein the second calculation formula includes:

[0048]

[0049] Among them, C e C represents the combined compressibility coefficient of water and rock. f C represents the rock compressibility coefficient. w S represents the compressibility coefficient of bound water. wi This indicates the degree of bound water saturation.

[0050] In some optional implementations of some embodiments, the step of calculating the first formation pressure includes:

[0051] The initial formation pressure, initial compressibility factor, dynamic reserves, and cumulative production from the gas well data are obtained, and the first formation pressure is calculated based on a preset third calculation formula, wherein the third calculation formula includes:

[0052]

[0053] in, p represents the first formation pressure. i Z represents the initial formation pressure. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This indicates the real-time cumulative output.

[0054] In some optional implementations of certain embodiments, calculating the real-time compressibility factor based on the gas well data and the first formation pressure includes:

[0055] Obtain the reservoir temperature, as well as the mole fraction, critical pressure, and critical temperature of each component alkane from the target gas well data;

[0056] The simulated comparative temperature and simulated comparative pressure of the target gas well are calculated based on the first formation pressure, the reservoir temperature, the mole fraction of each component alkane, the critical pressure, and the critical temperature.

[0057] The real-time compression factor is determined based on the proposed comparison temperature and proposed comparison pressure.

[0058] In some optional implementations of certain embodiments, the steps of calculating the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well include:

[0059] According to the preset fourth calculation formula, the reservoir temperature, the mole fraction of each alkane component, the critical pressure and critical temperature, and the first formation pressure are used to calculate the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well, wherein the fourth calculation formula includes:

[0060] p pr =p / ∑y i p ci

[0061] T pr =T / ∑y i T ci

[0062] Where, p pr The pressure to be compared is indicated by p, where p represents the pressure of the first formation, and y represents the pressure of the first formation. i p represents the mole fraction of each individual alkane component. ci T represents the critical pressure of each individual alkane component. pr The relative temperature is T, where T represents the reservoir temperature, and t represents the relative temperature. ci This indicates the critical temperature of each individual alkane component.

[0063] In some optional implementations of certain embodiments, the step of iteratively optimizing the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure includes:

[0064] Calculate the absolute difference between the first and second formation pressures in the previous test.

[0065] If the absolute value difference is greater than the preset judgment threshold, the second formation pressure of the current time is determined as the first formation pressure of the next time, and the step of calculating the real-time compressibility factor based on the gas well data and the first formation pressure is re-executed.

[0066] In some optional implementations of some embodiments, the apparatus further includes:

[0067] The correction module is used to import the target formation pressure into the trained fitting model for correction to obtain the corrected formation pressure, wherein the fitting model is trained based on multiple calculated historical formation pressures.

[0068] A third aspect of this disclosure provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0069] A fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0070] A fifth aspect of this disclosure provides a computer program product comprising a computer program or instructions that, when executed by a processor, implement the steps of the method described above.

[0071] By acquiring gas well data of a target gas well under abnormal high pressure and calculating a first formation pressure; calculating a real-time compressibility factor based on the gas well data and the first formation pressure; calculating a second formation pressure based on the real-time compressibility factor and the first formation pressure; and iteratively optimizing the second formation pressure according to the first formation pressure and a preset comparison threshold to obtain the target formation pressure, the calculation accuracy of formation pressure for abnormal high-pressure gas wells can be greatly improved. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 This is a schematic diagram of an application scenario of the method for calculating formation pressure in abnormally high-pressure tight gas wells according to the embodiments of this disclosure;

[0074] Figure 2 This is a flowchart of some embodiments of a method for calculating formation pressure in an abnormally high-pressure tight gas well according to the present disclosure;

[0075] Figure 3 This is a flowchart of some embodiments of another method for calculating formation pressure in abnormally high-pressure tight gas wells provided according to the embodiments of this disclosure;

[0076] Figure 4 This is a simplified schematic diagram of data fitting in some embodiments of another method for calculating formation pressure in abnormally high-pressure tight gas wells provided according to the embodiments of this disclosure;

[0077] Figure 5 This is a flowchart of some embodiments of a method for calculating formation pressure in an abnormally high-pressure tight gas well according to the present disclosure;

[0078] Figure 6This is a simplified structural diagram of a formation pressure calculation device for an abnormally high-pressure tight gas well according to an embodiment of the present disclosure;

[0079] Figure 7 This is a schematic diagram of an electronic device provided according to an embodiment of the present disclosure. Detailed Implementation

[0080] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0081] It should also be noted that, for ease of description, only the parts relevant to this disclosure are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0082] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different systems, devices, modules or units, and are not used to limit the order of functions performed by these systems, devices, modules or units or their interdependencies.

[0083] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0084] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0085] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0086] Example 1:

[0087] Figure 1 This is a schematic diagram of an application scenario of the method for calculating formation pressure in abnormally high-pressure tight gas wells according to some embodiments of the present disclosure.

[0088] exist Figure 1 In the application scenario, firstly, the computing device 101 can obtain the gas well data 102 of the target gas well under abnormal high pressure and calculate the first formation pressure 103.

[0089] Secondly, the computing device 101 can calculate the real-time compressibility factor 104 based on the gas well data 102 and the first formation pressure 103;

[0090] Next, based on the real-time compression factor 104 and the first formation pressure 103, the second formation pressure 105 is calculated;

[0091] Finally, the computing device 101 can iteratively calculate the first formation pressure 103 and the second formation pressure 105 based on a preset comparison threshold to obtain the target formation pressure 106.

[0092] It should be noted that the aforementioned computing device 101 can be either hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is software, it can be installed within the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0093] It should be understood that Figure 1 The number of computing devices shown is merely illustrative. Any number of computing devices can be used depending on implementation needs.

[0094] Example 2:

[0095] Continue to refer to Figure 2 The diagram illustrates flow 200 of some embodiments of the method for calculating formation pressure in abnormally high-pressure tight gas wells according to this disclosure. This method can be... Figure 1 The calculation is performed by the computing device 101. The method for calculating the formation pressure of an abnormally high-pressure tight gas well includes the following steps:

[0096] Step 201: Obtain the gas well data of the target gas well under abnormal high pressure and calculate the first formation pressure.

[0097] In some optional implementations of some embodiments, the execution subject of the abnormal high-pressure tight gas well formation pressure calculation method (e.g. Figure 1The computing device 101 shown can connect to the target device via a wired or wireless connection, then acquire gas well data of the target gas well under abnormal high pressure conditions, and calculate the first formation pressure. The gas well data can refer to fixed gas well / formation parameters, or gas well / formation parameters at the initial stage of production (also fixed values), or gas well / formation parameters collected in real time during gas production. The target gas well can be a sandstone gas well, a carbonate gas well, a volcanic gas well, etc. In the first calculation, the first formation pressure can refer to the initial data of the formation pressure calculated based on the gas well data. This initial data has a certain deviation from the target data and is used as basic data. In iterative calculations, the first formation pressure is replaced by the subsequently calculated second formation pressure and used as basic data in the recalculation. The aforementioned wireless connection methods can include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultrawideband) connections, and other currently known or future-developed wireless connection methods.

[0098] In some optional implementations of some embodiments, the step of calculating the first formation pressure includes:

[0099] The initial formation pressure, initial compressibility factor, dynamic reserves, and cumulative production from the gas well data are obtained, and the first formation pressure is calculated based on a preset third calculation formula, wherein the third calculation formula includes:

[0100]

[0101] in, p represents the first formation pressure. i Z represents the initial formation pressure. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This indicates the real-time cumulative output.

[0102] Cumulative production refers to the total amount of gas produced by gas wells in real-time statistics. Dynamic reserves refer to the remaining recoverable reserves of the target gas well in real-time statistics. Initial compressibility factor refers to the compressibility factor based on the initial gas production of the target gas well (approximately the initial state of the target gas well). The compressibility factor can also refer to a correction factor that must be considered when applying the ideal gas equation of state to real gases, used to represent the volume deviation of real gas after compression compared to ideal gas after compression under the same pressure.

[0103] Step 202: Calculate the real-time compressibility factor based on the gas well data and the first formation pressure.

[0104] The real-time compressibility factor refers to the compressibility factor calculated based on the first formation pressure and partial data from the gas well data. The real-time compressibility factor represents the volume deviation between the actual gas being compressed and the ideal gas being compressed under the same pressure during the gas production process of the target gas well.

[0105] Step 203: Calculate the second formation pressure based on the real-time compression factor and the first formation pressure.

[0106] Step 204: Based on the first formation pressure and a preset comparison threshold, iteratively optimize the second formation pressure to obtain the target formation pressure.

[0107] Iterative calculation refers to the process of continuously optimizing the calculation of the second formation pressure based on the first formation pressure and a correlation threshold. The correlation threshold can be a pre-set limit value used to optimize the second formation pressure. This iterative optimization method can be a difference optimization method based on the difference between the first and second formation pressures, a ratio optimization method based on the ratio of the first and second formation pressures, or other methods for optimizing the relationship between the first and second formation pressures, as needed. No further restrictions are imposed here.

[0108] The beneficial effects of one of the embodiments described above in this disclosure include at least the following:

[0109] By acquiring gas well data of a target gas well under abnormal high pressure and calculating a first formation pressure; calculating a real-time compressibility factor based on the gas well data and the first formation pressure; calculating a second formation pressure based on the real-time compressibility factor and the first formation pressure; and iteratively optimizing the second formation pressure according to the first formation pressure and a preset comparison threshold to obtain the target formation pressure, the calculation accuracy of formation pressure for abnormal high-pressure gas wells can be greatly improved.

[0110] Example 3:

[0111] Continue to refer to Figure 3 The diagram illustrates flow 300 of some embodiments of the method for calculating formation pressure in abnormally high-pressure tight gas wells according to this disclosure. This method can be... Figure 1 The calculation is performed by the computing device 101. The method for calculating the formation pressure of an abnormally high-pressure tight gas well includes the following steps:

[0112] Step 301: Obtain the gas well data of the target gas well under abnormal high pressure and calculate the first formation pressure.

[0113] Step 302: Calculate the real-time compressibility factor based on the gas well data and the first formation pressure.

[0114] Step 303: Calculate the combined water-rock compressibility coefficient based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data.

[0115] The bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation are all commonly used coefficients in this field and will not be elaborated upon here. The bound water saturation remains approximately constant during the production of the target gas well, and therefore can be considered a constant coefficient. The combined water-rock compressibility coefficient refers to the combined compressibility coefficient of bound water and rock. This coefficient comprehensively reflects the relevant water-rock conditions in the gas well.

[0116] In some optional implementations, the step of calculating the combined water-rock compressibility coefficient based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data includes: calculating the combined water-rock compressibility coefficient according to a preset second calculation formula, and the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data, wherein the second calculation formula includes:

[0117]

[0118] Among them, C e C represents the combined compressibility coefficient of water and rock. f C represents the rock compressibility coefficient. w S represents the compressibility coefficient of bound water. wi This indicates the degree of bound water saturation.

[0119] Step 304: Calculate the second formation pressure based on the preset first calculation formula, the real-time compressibility factor, the water-rock composite compressibility coefficient, and the initial compressibility factor, dynamic reserves, and cumulative production in the gas well data. The first calculation formula includes:

[0120]

[0121] Where, p r The real-time formation pressure represented by C e p represents the combined compressibility coefficient of water and rock. i Z represents the initial formation pressure, and Z represents the real-time compressibility factor. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This represents the real-time cumulative production. A more accurate result for formation pressure can be obtained through this calculation formula.

[0122] Step 305: Based on the first formation pressure and a preset comparison threshold, the second formation pressure is iteratively optimized to obtain the target formation pressure.

[0123] In some optional implementations, the step of iteratively optimizing the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure includes: calculating the absolute difference between the previous first formation pressure and the second formation pressure; if the absolute difference is greater than a preset judgment threshold, determining the current second formation pressure as the next first formation pressure, and re-executing the step of calculating the real-time compressibility factor based on the gas well data and the first formation pressure. Choosing the absolute difference iteration method involves less computation and higher accuracy, making it more suitable for calculating the actual situation of abnormally high-pressure gas wells, and is therefore a preferred choice.

[0124] Step 306: The target formation pressure is imported into the trained fitting model for correction to obtain the corrected formation pressure, wherein the fitting model is trained based on multiple calculated historical formation pressures.

[0125] To further improve the accuracy of the calculation, this embodiment of the disclosure fits the target formation pressure obtained from multiple calculations. The historical formation pressure can refer to the numerical value of the target formation pressure obtained through the aforementioned steps. Figure 4 A schematic diagram of the fitting calculation is shown. The horizontal axis represents the target formation pressure calculated by the embodiments of this disclosure, and the vertical axis represents the formation pressure obtained by pressure recovery interpretation (which can be approximately considered as the standard value). In the figure, the small blue dots represent multiple calculated historical formation pressures, and the black diagonal lines represent the straight lines of linear fitting.

[0126] In some specific embodiments, y = 0.7808x + 3.1093. Here, y represents the pressure recovery explained formation pressure, and x represents the calculated target formation pressure.

[0127] In some alternative implementations of some embodiments, steps 301-306 are related to... Figure 2 The specific implementation of the corresponding steps in those embodiments and the resulting technical effects can be found in the following references. Figure 2 The steps involved will not be elaborated upon here.

[0128] Example 4:

[0129] Continue to refer to Figure 5 The diagram illustrates flow 400 of some embodiments of a method for calculating formation pressure in abnormally high-pressure tight gas wells according to this disclosure. This method can be... Figure 1 The calculation is performed by the computing device 101. The method for calculating the formation pressure of an abnormally high-pressure tight gas well includes the following steps:

[0130] Step 401: Obtain the gas well data of the target gas well under abnormal high pressure and calculate the first formation pressure.

[0131] Step 402: Calculate the real-time compressibility factor based on the gas well data and the first formation pressure.

[0132] Step 403: Obtain the reservoir temperature, as well as the mole fraction, critical pressure, and critical temperature of each alkane component from the target gas well data.

[0133] Reservoir temperature refers to the measured temperature of the bottom layer of the reservoir in the target gas well. This temperature can be approximated as constant during gas production. The gas extracted from the target gas well mainly consists of a mixture of various alkanes. After gas production is completed, it is necessary to separate the individual alkanes and calculate their respective parameters, such as mole fraction, critical pressure, and critical temperature.

[0134] Step 404: Calculate the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well based on the first formation pressure, the reservoir temperature, the mole fraction of each component alkane, the critical pressure, and the critical temperature.

[0135] In some optional implementations, the steps of calculating the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well include:

[0136] According to the preset fourth calculation formula, the reservoir temperature, the mole fraction of each alkane component, the critical pressure and critical temperature, and the first formation pressure are used to calculate the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well, wherein the fourth calculation formula includes:

[0137] p pr =p / ∑y i p ci

[0138] T pr =T / ∑y i T ci

[0139] Where, p pr The pressure to be compared is indicated by p, where p represents the pressure of the first formation, and y represents the pressure of the first formation. i p represents the mole fraction of each individual alkane component. ci T represents the critical pressure of each individual alkane component. pr The relative temperature is T, where T represents the reservoir temperature, and t represents the relative temperature. ci This indicates the critical temperature of each individual alkane component.

[0140] Step 405: Determine the real-time compression factor based on the simulated comparison temperature and simulated comparison pressure.

[0141] Based on the simulated comparison temperature and simulated comparison pressure obtained in step 404, the real-time compressibility factor can be calculated or screened. This calculation or screening process can utilize commonly used techniques in the field, such as the Standing-Katz chart lookup method, or calculate the real-time compressibility factor using methods like Hall-Yarborough or Dranchuk-Abou-Kassem. Other methods can also be used to determine the real-time compressibility factor; these can be set as needed without specific limitations.

[0142] Step 406: Calculate the combined water-rock compressibility coefficient based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data.

[0143] Step 407: Calculate the second formation pressure based on the preset first calculation formula, the real-time compression factor, the water-rock integrated compression coefficient, and the initial compression factor, dynamic reserves, and cumulative production in the gas well data.

[0144] Step 408: Based on the first formation pressure and a preset comparison threshold, the second formation pressure is iteratively optimized to obtain the target formation pressure.

[0145] Step 409: The target formation pressure is imported into the trained fitting model for correction to obtain the corrected formation pressure. The fitting model is trained based on multiple calculated historical formation pressures.

[0146] In some alternative implementations of some embodiments, steps 401-409 are related to... Figure 2 or Figure 3 The specific implementation of the corresponding steps in those embodiments and the resulting technical effects can be found in the following references. Figure 2 or Figure 3 The steps involved will not be elaborated upon here.

[0147] Example 5:

[0148] Further reference Figure 6 As an implementation of the above figures and methods, this disclosure provides some embodiments of an abnormally high-pressure tight gas well formation pressure calculation device. These device embodiments are similar to... Figure 2 The above-described method embodiments correspond to these.

[0149] like Figure 6 As shown, the abnormal high-pressure tight gas well formation pressure calculation device 1000 in some embodiments includes:

[0150] The first calculation module 1001 is used to acquire gas well data of the target gas well under abnormal high pressure and calculate the first formation pressure.

[0151] The second calculation module 1002 is used to calculate the real-time compressibility factor based on the gas well data and the first formation pressure.

[0152] The third calculation module 1003 is used to calculate the second formation pressure based on the real-time compression factor and the first formation pressure;

[0153] The optimization module 1004 is used to iteratively optimize the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure.

[0154] In some optional implementations of certain embodiments, calculating the second formation pressure based on the real-time compressibility factor and the first formation pressure includes:

[0155] The combined water-rock compressibility coefficient is calculated based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data.

[0156] The second formation pressure is calculated based on the preset first calculation formula, the real-time compressibility factor, the water-rock composite compressibility coefficient, and the initial compressibility factor, dynamic reserves, and cumulative production in the gas well data. The first calculation formula includes:

[0157]

[0158] Where, p r The real-time formation pressure represented by C e p represents the combined compressibility coefficient of water and rock. i Z represents the initial formation pressure, and Z represents the real-time compressibility factor. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This indicates the real-time cumulative output.

[0159] In some optional implementations of certain embodiments, the calculation of the combined water-rock compressibility coefficient based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data includes:

[0160] Based on the preset second calculation formula, and the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data, the water-rock composite compressibility coefficient is calculated, wherein the second calculation formula includes:

[0161]

[0162] Among them, C e C represents the combined compressibility coefficient of water and rock.f C represents the rock compressibility coefficient. w S represents the compressibility coefficient of bound water. wi This indicates the degree of bound water saturation.

[0163] In some optional implementations of some embodiments, the step of calculating the first formation pressure includes:

[0164] The initial formation pressure, initial compressibility factor, dynamic reserves, and cumulative production from the gas well data are obtained, and the first formation pressure is calculated based on a preset third calculation formula, wherein the third calculation formula includes:

[0165]

[0166] in, p represents the first formation pressure. i Z represents the initial formation pressure. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This indicates the real-time cumulative output.

[0167] In some optional implementations of certain embodiments, calculating the real-time compressibility factor based on the gas well data and the first formation pressure includes:

[0168] Obtain the reservoir temperature, as well as the mole fraction, critical pressure, and critical temperature of each component alkane from the target gas well data;

[0169] The simulated comparative temperature and simulated comparative pressure of the target gas well are calculated based on the first formation pressure, the reservoir temperature, the mole fraction of each component alkane, the critical pressure, and the critical temperature.

[0170] The real-time compression factor is determined based on the proposed comparison temperature and proposed comparison pressure.

[0171] In some optional implementations of certain embodiments, the steps of calculating the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well include:

[0172] According to the preset fourth calculation formula, the reservoir temperature, the mole fraction of each alkane component, the critical pressure and critical temperature, and the first formation pressure are used to calculate the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well, wherein the fourth calculation formula includes:

[0173] p pr =p / ∑y i p ci

[0174] T pr =T / ∑y i T ci

[0175] Where, p pr The pressure to be compared is indicated by p, where p represents the pressure of the first formation, and y represents the pressure of the first formation. i p represents the mole fraction of each individual alkane component. ci T represents the critical pressure of each individual alkane component. pr The relative temperature is T, where T represents the reservoir temperature, and t represents the relative temperature. ci This indicates the critical temperature of each individual alkane component.

[0176] In some optional implementations of certain embodiments, the step of iteratively optimizing the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure includes:

[0177] Calculate the absolute difference between the first and second formation pressures in the previous test.

[0178] If the absolute value difference is greater than the preset judgment threshold, the second formation pressure of the current time is determined as the first formation pressure of the next time, and the step of calculating the real-time compressibility factor based on the gas well data and the first formation pressure is re-executed.

[0179] In some optional implementations of some embodiments, the apparatus further includes:

[0180] The correction module is used to import the target formation pressure into the trained fitting model for correction to obtain the corrected formation pressure, wherein the fitting model is trained based on multiple calculated historical formation pressures.

[0181] It is understandable that the modules described in the device 1000 are similar to those in the reference. Figure 2 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the device 1000 and the modules contained therein, and will not be repeated here.

[0182] Example 6:

[0183] like Figure 7 As shown, electronic device 1100 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 1101, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 1102 or a program loaded from storage device 1108 into random access memory (RAM) 1103. The RAM 1103 also stores various programs and data required for the operation of electronic device 1100. The processing device 1101, ROM 1102, and RAM 1103 are interconnected via bus 1104. Input / output (I / O) interface 1105 is also connected to bus 1104.

[0184] Typically, the following devices can be connected to I / O interface 1105: input devices 1106 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 1107 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1108 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1109. Communication device 1109 allows electronic device 1100 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 An electronic device 1100 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 7 Each box shown can represent a device or multiple devices as needed.

[0185] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program or instructions carried on a computer-readable medium, the computer program or instructions containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 1109, or installed from storage device 1108, or installed from ROM 1102. When the computer program is executed by processing device 1101, it performs the functions defined above in the methods of some embodiments of this disclosure.

[0186] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0187] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0188] The aforementioned computer-readable medium may be included in the aforementioned device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquire gas well data of the target gas well under abnormal high pressure conditions and calculate the first formation pressure;

[0189] Calculate the real-time compressibility factor based on the gas well data and the first formation pressure;

[0190] The second formation pressure is calculated based on the real-time compressibility factor and the first formation pressure.

[0191] Based on the first formation pressure and a preset comparison threshold, the second formation pressure is iteratively optimized to obtain the target formation pressure.

[0192] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0193] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0194] The modules described in some embodiments of this disclosure can be implemented in software or hardware. The described modules can also be located in a processor, for example, and can be described as:

[0195] The system comprises a first calculation module, a second calculation module, a third calculation module, and an optimization module. For example, the first calculation module can also be described as "a module for acquiring gas well data of a target gas well under abnormal high pressure and calculating the first formation pressure".

[0196] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0197] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for calculating formation pressure in abnormally high-pressure gas wells, characterized in that, include: Obtain gas well data for the target gas well under abnormal high pressure conditions and calculate the first formation pressure; Calculate the real-time compressibility factor based on the gas well data and the first formation pressure; The second formation pressure is calculated based on the real-time compressibility factor and the first formation pressure. Based on the first formation pressure and a preset comparison threshold, the second formation pressure is iteratively optimized to obtain the target formation pressure.

2. The method according to claim 1, characterized in that, Based on the real-time compressibility factor and the first formation pressure, the second formation pressure is calculated, including: The combined water-rock compressibility coefficient is calculated based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data. The second formation pressure is calculated based on the preset first calculation formula, the real-time compressibility factor, the water-rock composite compressibility coefficient, and the initial compressibility factor, dynamic reserves, and cumulative production in the gas well data. The first calculation formula includes: Where, p r The real-time formation pressure represented by C e p represents the combined compressibility coefficient of water and rock. i Z represents the initial formation pressure, and Z represents the real-time compressibility factor. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This indicates the real-time cumulative output.

3. The method according to claim 2, characterized in that, The calculation of the combined water-rock compressibility coefficient based on the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data includes: Based on the preset second calculation formula, and the bound water compressibility coefficient, rock compressibility coefficient, and bound water saturation in the gas well data, the water-rock composite compressibility coefficient is calculated, wherein the second calculation formula includes: Among them, C e C represents the combined compressibility coefficient of water and rock. f C represents the rock compressibility coefficient. w S represents the compressibility coefficient of bound water. wi This indicates the degree of bound water saturation.

4. The method according to claim 1, characterized in that, The steps for calculating the first formation pressure include: The initial formation pressure, initial compressibility factor, dynamic reserves, and cumulative production from the gas well data are obtained, and the first formation pressure is calculated based on a preset third calculation formula, wherein the third calculation formula includes: in, p represents the first formation pressure. i Z represents the initial formation pressure. i G represents the initial compressibility factor, and G represents the dynamic reserves. p This indicates the real-time cumulative output.

5. The method according to claim 1, characterized in that, Based on the gas well data and the first formation pressure, the real-time compressibility factor is calculated, including: Obtain the reservoir temperature, as well as the mole fraction, critical pressure, and critical temperature of each component alkane from the target gas well data; The simulated comparative temperature and simulated comparative pressure of the target gas well are calculated based on the first formation pressure, the reservoir temperature, the mole fraction of each component alkane, the critical pressure, and the critical temperature. The real-time compression factor is determined based on the proposed comparison temperature and proposed comparison pressure.

6. The method according to claim 5, characterized in that, The steps for calculating the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well include: According to the preset fourth calculation formula, the reservoir temperature, the mole fraction of each alkane component, the critical pressure and critical temperature, and the first formation pressure are used to calculate the pseudo-comparison temperature and pseudo-comparison pressure of the target gas well, wherein the fourth calculation formula includes: p pr =p / ∑y i p ci T pr =T / ∑y i T ci Where, p pr The pressure to be compared is indicated by p, where p represents the pressure of the first formation, and y represents the pressure of the first formation. i p represents the mole fraction of each individual alkane component. ci T represents the critical pressure of each individual alkane component. pr The relative temperature is T, where T represents the reservoir temperature, and t represents the relative temperature. ci This indicates the critical temperature of each individual alkane component.

7. The method according to claim 1, characterized in that, The step of iteratively optimizing the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure includes: Calculate the absolute difference between the first and second formation pressures in the previous test. If the absolute value difference is greater than the preset judgment threshold, the second formation pressure of the current time is determined as the first formation pressure of the next time, and the step of calculating the real-time compressibility factor based on the gas well data and the first formation pressure is re-executed.

8. The method according to any one of claims 1 to 7, characterized in that, Also includes: The target formation pressure is imported into the trained fitting model for correction to obtain the corrected formation pressure. The fitting model is trained based on multiple calculated historical formation pressures.

9. A device for calculating formation pressure in abnormally high-pressure tight gas wells, characterized in that, include: The first calculation module is used to acquire gas well data of the target gas well under abnormal high pressure and calculate the first formation pressure. The second calculation module is used to calculate the real-time compressibility factor based on the gas well data and the first formation pressure. The third calculation module is used to calculate the second formation pressure based on the real-time compression factor and the first formation pressure; The optimization module is used to iteratively optimize the second formation pressure based on the first formation pressure and a preset comparison threshold to obtain the target formation pressure.

10. An electronic 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 steps of the method as described in any one of claims 1 to 8.

11. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 8.

12. A computer program product, said computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method as described in any one of claims 1 to 8.

Images