Method and device for determining water yield of ultra-deep gas well

Abstract

The invention provides a method and device for determining the water yield of an ultra-deep gas well, and relates to the field of oil and gas field development, and the method comprises the steps: inputting the obtained environment parameters of the ultra-deep gas well into a pre-constructed water yield prediction model, and obtaining an initial prediction value of the water yield; wherein the gas well environment parameters comprise real-time gas production rate, reservoir outer boundary pressure, bottom hole flowing pressure, gas-water physical property parameters and formation temperature; determining a water yield correction factor according to the obtained gas-water relative permeability curve; and correcting the initial predicted value by using the water yield correction factor to obtain a final predicted value of the water yield. According to the method, the water yield can be directly calculated only by using the gas yield and the production pressure difference through equivalent replacement of the gas-water seepage parameters on the basis of the gas well productivity equation.

Description

Technical Field

[0001] The present application relates to the field of oil and gas field development, and specifically to a method for determining water production in an ultra-deep gas well. Background Art

[0002] During oil and gas field development, accurately predicting gas well water production is crucial for optimizing production processes (such as sand control, water management, and equipment corrosion prevention) and formulating development strategies. Currently, existing methods for estimating water production based on gas production mainly include empirical formulas, statistical models, and physical models. However, existing technologies still have the following limitations:

[0003] The empirical formula method achieves rapid estimation by establishing a fixed ratio (e.g., water-gas ratio, WGR) or a decreasing pattern (e.g., exponential decrease) between gas and water production. However, this assumes stringent conditions and requires a stable water source (e.g., condensate or uniform water intrusion). In practice, water intrusion dynamics are complex (e.g., fracture intrusion and water coning at the edge and bottom), causing the ratio parameter (WGR) to drift significantly over production time. Furthermore, it has poor adaptability and cannot distinguish between different water sources (e.g., formation water and condensate), resulting in significant errors in water production predictions after intensified water intrusion or after manual intervention (e.g., water plugging).

[0004] Statistical modeling (such as production data regression analysis): Utilize historical data to establish a statistical relationship between gas and water production (linear or nonlinear regression model), achieving data-driven predictions. However, this method is highly data-dependent and requires a large amount of continuous, high-quality production data. Data noise or missing data can easily lead to model overfitting or failure. Furthermore, there is a risk of extrapolation, and the model is only applicable to the scope of historical data coverage. Predictions in the middle and late stages of development or under extreme conditions (such as the transition from high-pressure gas reservoirs to low pressure) are unreliable. The lack of physical mechanisms ignores the geological characteristics of the gas reservoir and the mechanisms of multiphase flow. The model has poor interpretability and is difficult to guide engineering decisions.

[0005] Physical model method (such as material balance method, two-phase flow model): Based on the principle of conservation of matter or the dynamics of gas-liquid two-phase flow in the wellbore (such as liquid holdup calculation), a physical-driven prediction model is constructed. This method has complex parameter requirements and requires accurate acquisition of the original geological reserves of the gas reservoir, water intrusion, fluid physical properties (density, viscosity) and wellbore parameters (pipe diameter, inclination). In actual applications, the cost of parameter acquisition is high and the uncertainty is large. The applicability of single wells is insufficient. The material balance method focuses on the overall analysis of the gas reservoir and it is difficult to accurately characterize the water production dynamics of a single well (such as local water breakthrough). The two-phase flow model relies on professional software for solution, making it difficult to achieve real-time prediction and placing stringent technical requirements on on-site operators.

[0006] This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. No statement herein is admitted to be prior art by virtue of its inclusion in this section. Summary of the Invention

[0007] In response to the problems in the prior art, the present application provides a method and device for determining the water production of ultra-deep gas wells. Based on the gas well production capacity equation, the method and device can directly calculate the water production using only the gas production and production pressure difference by equivalently replacing the gas-water seepage parameters.

[0008] To solve the above technical problems, this application provides the following technical solutions:

[0009] In a first aspect, the present application provides a method for determining water production in an ultra-deep gas well, comprising:

[0010] Inputting the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial predicted value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottomhole flowing pressure, gas and water physical properties and formation temperature;

[0011] Determine the water production correction factor based on the obtained gas-water relative permeability curve;

[0012] The initial predicted value is corrected using the water production correction factor to obtain a final predicted value of water production.

[0013] Furthermore, the gas-water physical parameters include gas viscosity, gas compressibility, water viscosity, and water compressibility; and the step of obtaining the ultra-deep gas well environmental parameters includes:

[0014] Obtain gas and water samples from ultra-deep gas well reservoirs;

[0015] Performing pressure, volume, and temperature tests on the gas sample to obtain the gas viscosity and gas compressibility of the gas sample under gas reservoir conditions;

[0016] The water samples are subjected to experimental analysis to obtain the water viscosity and water compressibility coefficient under the formation temperature and production pressure differential conditions at the time of sampling.

[0017] Furthermore, the step of pre-building the water production prediction model includes:

[0018] Generate a gas production prediction model based on the permeability of the gas reservoir rock of the ultra-deep gas well, the effective thickness of the reservoir, the oil drainage radius, the wellbore radius, the outer boundary pressure of the reservoir, the bottom hole flowing pressure, the formation temperature, the gas viscosity and the gas compressibility coefficient;

[0019] The water production prediction model is constructed according to the gas production prediction model, the water viscosity and the water compressibility coefficient.

[0020] Furthermore, the use of the water production correction factor to correct the initial prediction value to obtain a final prediction value of water production includes:

[0021] Establish the proportional relationship between water production and gas production;

[0022] Obtaining a conversion value of gas production according to the initial predicted value and the proportional relationship;

[0023] The product of the converted value of the gas production and the water production correction factor is determined as the final predicted value.

[0024] In a second aspect, the present application provides a device for determining water production in an ultra-deep gas well, comprising:

[0025] An initial prediction unit is used to input the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial predicted value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottom hole flowing pressure, gas and water physical properties and formation temperature;

[0026] A correction factor determination unit, used to determine a water production correction factor based on the obtained gas-water relative permeability curve;

[0027] The final prediction unit is used to correct the initial prediction value using the water production correction factor to obtain a final prediction value of the water production.

[0028] Furthermore, the gas-water physical property parameters include gas viscosity, gas compressibility, water viscosity and water compressibility; and the initial prediction unit includes:

[0029] Gas and water sample acquisition module, used to obtain gas and water samples from ultra-deep gas well reservoirs;

[0030] A gas sample parameter determination module is used to perform pressure, volume, and temperature tests on the gas sample to obtain the gas viscosity and gas compressibility of the gas sample under gas reservoir conditions;

[0031] The water sample parameter determination module is used to perform experimental analysis on the water sample to obtain the water viscosity and water compressibility coefficient under the formation temperature and production pressure difference conditions at the time of sampling.

[0032] Furthermore, the initial prediction unit includes:

[0033] A gas production model generation module is used to generate a gas production prediction model based on the permeability of the gas reservoir rock of the ultra-deep gas well, the effective thickness of the reservoir, the oil drainage radius, the wellbore radius, the outer boundary pressure of the reservoir, the bottom hole flowing pressure, the formation temperature, the gas viscosity and the gas compressibility coefficient;

[0034] The water production model generation module is used to construct the water production prediction model according to the gas production prediction model, the water viscosity and the water compressibility coefficient.

[0035] Furthermore, the final prediction unit includes:

[0036] A proportional relationship establishment module is used to establish the proportional relationship between water production and gas production;

[0037] A converted gas volume determination module, configured to obtain a converted value of the gas production volume based on the initial predicted value and the proportional relationship;

[0038] The final prediction module is used to determine the product of the converted value of the gas production and the water production correction factor as the final prediction value.

[0039] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for determining water production in an ultra-deep gas well are implemented.

[0040] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for determining water production in an ultra-deep gas well.

[0041] In a fifth aspect, the present application provides a computer program product, comprising a computer program / instruction, which, when executed by a processor, implements the steps of the method for determining water production in an ultra-deep gas well.

[0042] In response to the problems in the prior art, the present application provides a method and device for determining water production in ultra-deep gas wells. This method can reflect the impact of changes in production pressure differential on water invasion in real time through a dynamic correction factor, and directly derive water production based on the gas-water seepage ratio, effectively overcoming the errors caused by static parameters or assumed conditions in traditional methods. It reduces dependence on data and simplifies parameter requirements. It only requires real-time gas production and production pressure differential data to achieve water production, without relying on large amounts of historical data. It directly uses known gas parameters for calculation through equivalent substitution theory, significantly reducing data acquisition costs and complexity. The calculation model can adapt to different water production sources (such as formation water, fracture inrush water) and dynamic water invasion conditions (such as after water plugging measures or water invasion intensification), breaking through the traditional empirical formula's reliance on a stable water-gas ratio, and is particularly suitable for the complex geological and development environments of ultra-deep gas wells. By transforming the gas well productivity equation, it incorporates gas and water production into a unified seepage framework, avoiding the redundant process of independent calculations of multiple models. On-site prediction results can be quickly output by simply calibrating the correction factors based on real-time data, reducing the need for complex experiments (such as high-frequency water phase physical property testing) and dedicated software. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 This is a flow chart of a method for determining water production in an ultra-deep gas well in an embodiment of the present application;

[0045] Figure 2 This is a flow chart for obtaining ultra-deep gas well environmental parameters in an embodiment of the present application;

[0046] Figure 3 This is a flow chart of constructing a water production prediction model in an embodiment of the present application;

[0047] Figure 4 This is a flow chart for obtaining the final predicted value of water production in the embodiment of the present application;

[0048] Figure 5 This is a structural diagram of a device for determining water production in an ultra-deep gas well according to an embodiment of the present application;

[0049] Figure 6 This is a structural diagram of the initial prediction unit in an embodiment of the present application;

[0050] Figure 7 This is a structural diagram of a correction factor determination unit in an embodiment of the present application;

[0051] Figure 8 This is a structural diagram of the final prediction unit in an embodiment of the present application;

[0052] Figure 9 A schematic diagram of the structure of an electronic device in an embodiment of the present application;

[0053] Figure 10 This is an overall flow chart of the method for determining water production in an ultra-deep gas well in an embodiment of the present application;

[0054] Figure 11 This is a schematic diagram of stable plane seepage in an embodiment of the present application. DETAILED DESCRIPTION

[0055] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0056] The information collected in the technical solution of this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data comply with the relevant laws, regulations and standards of relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0057] Provide users with corresponding operation entrances for them to choose to agree or reject the automated decision-making results; if the user chooses to reject, they will enter the expert decision-making process.

[0058] In one embodiment, see Figure 1 In order to directly calculate water production using only gas production and production pressure differential based on the gas well productivity equation by equivalently replacing gas-water seepage parameters, this application provides a method for determining water production in ultra-deep gas wells, including:

[0059] S101: Inputting the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial predicted value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottom hole flowing pressure, gas and water physical properties, and formation temperature;

[0060] S102: determining a water production correction factor based on the obtained gas-water relative permeability curve;

[0061] S103: Correcting the initial prediction value using the water production correction factor to obtain a final prediction value of water production.

[0062] It is understandable that the embodiment of the present application, by modifying the gas well productivity equation, establishes a correlation model of gas and water production under the same seepage framework, thus avoiding the independent use of gas and water prediction formulas. g , production pressure difference ΔP) and gas physical properties data (μ g ,z g ), the water phase parameters (μ w ,z w ), eliminating the need for independent measurements of water phase properties and resolving parameter redundancy issues. Furthermore, embedding the production pressure differential as a dynamic variable in the model reflects changes in the gas-water two-phase seepage ratio in real time, enhancing the dynamic adaptability of water production prediction.

[0063] Specifically, by introducing the water phase physical property parameters (μ w ,z w) Dynamically characterize the water production mechanism. Breaking through the limitation of condensate water / formation water mixed production, equivalent modeling of different water production sources (such as fracture water channeling, edge and bottom water coning) is achieved through parameter replacement. Its equation directly relates the current production pressure difference (ΔP) to the water phase flow capacity, avoiding the failure problem of the water-gas ratio parameter (Water-to-Gas Ratio, referred to as WGR) after artificial intervention (water plugging). It replaces pure data fitting with a physically driven seepage equation to reduce dependence on historical data. Only single well gas production (Q g ) and production pressure difference (ΔP) data to calculate the water production (Q w ).

[0064] The present invention proposes a method for determining the drainage volume of ultra-deep gas wells. The method is based on the gas well productivity equation and achieves the goal of using only the gas production volume (Q g ) and production pressure difference (ΔP) to directly calculate the water production (Q w ), the core innovations include:

[0065] (1) Equivalent transformation of gas-water seepage equation:

[0066] The gas well productivity formula is:

[0067]

[0068] Gas physical parameters (μ g ,z g ) is replaced by the water phase parameter (μ w ,z w ), construct the water production calculation equation:

[0069]

[0070] Where K represents the permeability of the reservoir rock (unit: mD), h represents the effective thickness of the reservoir, and P e represents the reservoir outer boundary pressure, P wf represents the bottom hole flowing pressure, T represents the reservoir temperature, μ g is the gas viscosity, is the mean value of the gas compressibility coefficient, μ w is the viscosity of water, is the mean water compressibility coefficient, r e is the oil leakage radius, r w is the wellbore radius.

[0071] (2) Parameter equivalent replacement theory:

[0072] Through the relationship between the gas-water two-phase seepage ratio, the correlation formula of gas and water production is established:

[0073]

[0074] Combined with known gas properties and measured gas production (Q g ), directly derive the water production:

[0075]

[0076] (3) Introducing the correction factor (f(ΔP)) of the production pressure difference (ΔP) to the gas-water relative permeability, the optimization formula is:

[0077]

[0078] Adaptive prediction under dynamic water invasion conditions is achieved by fitting f(ΔP) with historical production data or determining f(ΔP) based on the acquired gas-water relative permeability curve.

[0079] The core of the embodiment of the present application is: based on the gas-water seepage equivalent substitution theory, by transforming the traditional gas well productivity equation, the gas physical property parameters (gas viscosity μ g , gas compressibility coefficient ) is replaced by water phase parameters (water viscosity μ w , water compressibility coefficient ), and introduce the dynamic difference correction factor (f(ΔP)) to achieve the utilization of gas production (Q g ) and production pressure difference (ΔP) to directly predict water production (Q w ).

[0080] Accurate water production prediction can optimize drainage plans, avoid the risk of excessive drainage or equipment corrosion, and improve gas field development efficiency. This method is suitable for ultra-deep gas reservoirs with high temperature and high pressure (such as the well depth exceeding 6,800 meters in the example), and can maintain stable prediction performance under extreme working conditions, providing a reliable basis for feasibility assessment of gas well conversion to drainage wells and supporting scientific development decisions for oil and gas fields. Through theoretical innovation and technological integration, the limitations of existing methods in terms of accuracy, adaptability, and cost are overcome, providing an efficient and reliable technical means for predicting the drainage volume of ultra-deep gas wells, which has important engineering application value.

[0081] As can be seen from the above description, the method for determining water production in ultra-deep gas wells provided by this application can reflect the impact of changes in production pressure differential on water invasion in real time through a dynamic correction factor, and directly derive water production based on the gas-water seepage ratio, effectively overcoming the errors caused by static parameters or assumptions in traditional methods. It reduces dependence on data and simplifies parameter requirements. It only requires real-time gas production and production pressure differential data to achieve water production, without relying on a large amount of historical data. It directly uses known gas parameters for calculation through equivalent substitution theory, significantly reducing data acquisition cost and complexity. This calculation model can adapt to different water production sources (such as formation water, fracture inrush water) and dynamic water invasion conditions (such as after water plugging measures or water invasion intensification), breaking through the traditional empirical formula's reliance on a stable water-gas ratio, and is particularly suitable for the complex geological and development environments of ultra-deep gas wells. By transforming the gas well productivity equation, it incorporates gas and water production into a unified seepage framework, avoiding the redundant process of independent calculations of multiple models. On-site prediction results can be quickly output by simply calibrating the correction factors based on real-time data, reducing the need for complex experiments (such as high-frequency water phase physical property testing) and dedicated software.

[0082] In one embodiment, see Figure 2 The gas-water physical parameters include gas viscosity, gas compressibility, water viscosity, and water compressibility; the step of obtaining the ultra-deep gas well environmental parameters includes:

[0083] S201: Obtain gas and water samples from the ultra-deep gas reservoir;

[0084] S202: performing pressure, volume, and temperature testing on the gas sample to obtain gas viscosity and gas compressibility of the gas sample under gas reservoir conditions;

[0085] S203: Experimentally analyzing the water sample to obtain the water viscosity and water compressibility under the formation temperature and production pressure differential conditions at the time of sampling.

[0086] Understandably, see Figure 10 To obtain gas viscosity, gas compressibility, water viscosity, and water compressibility, perform the following steps:

[0087] Step 1: Collect geological and logging data of the gas reservoir and obtain gas and water samples from the gas reservoir.

[0088] Step 2: Under laboratory conditions, the temperature-pressure (PV) relationship and gas compressibility of the gas sample under reservoir conditions are measured by the pressure-volume-temperature (PVT) test method to obtain the gas viscosity (μ g ) and gas compressibility coefficient

[0089] Step 3: The obtained water samples were subjected to experimental analysis. In order to ensure the accuracy of the experiment, the experimental data were normalized and the water viscosity and compressibility under laboratory conditions were converted into water viscosity under the conditions of formation temperature and production pressure difference at the time of sampling (μ w ) and water compressibility

[0090] In addition, the gas production (Q g ), production pressure difference (ΔP=P e -P wf ) and formation temperature (T) can be directly obtained through instruments or formation temperature data curves.

[0091] When performing step 1, the sample label must include the well number, depth, sampling time, pressure / temperature conditions, and be aligned with the depth of the logging curve. When collecting gas samples, a high-pressure PVT cylinder must be used to maintain the formation pressure to avoid changes in gas composition (such as condensation of heavy components) caused by pressure reduction.

[0092] Water samples should be collected using oxygen-free sampling bottles (pre-filled with inert gas), filtered on-site (0.45μm filter membrane) to remove suspended solids, and stabilized with HgCl2 to inhibit microbial activity. The pressure, temperature, and flow rate during sampling should be recorded to ensure that the water sample is in a single-phase flow state.

[0093] When performing step 2, ensure that the gas is always in a single-phase flow state during the experiment to avoid condensation caused by pressure or temperature changes. The calculation of the gas compressibility coefficient should use the state equation suitable for the gas reservoir composition (such as the PR or SRK equation). The PR and SRK equations are both cubic state equations, and their general form is: Where: P is pressure, T is temperature, V is molar volume, R is the gas constant, a(T) is the attractive term, which is temperature-dependent, b is the repulsive term, which is molecular volume-dependent, and c is the equation type constant. Finally, enter the exact critical temperature, pressure, and eccentricity factor.

[0094] When performing step 3, the viscosity can be corrected for temperature dependence using the Arrhenius equation or the VFT model; the compressibility can be extrapolated from laboratory atmospheric pressure data to high-pressure formation conditions using the Tait equation.

[0095] It can be seen from the above description that the method for determining the water production of an ultra-deep gas well provided in this application can obtain the environmental parameters of the ultra-deep gas well.

[0096] In one embodiment, see Figure 3 The step of pre-building the water production prediction model includes:

[0097] S301: Generate a gas production prediction model based on the permeability of the gas reservoir rock of the ultra-deep gas well, the effective reservoir thickness, the oil drainage radius, the wellbore radius, the reservoir outer boundary pressure, the bottom hole flowing pressure, the formation temperature, the gas viscosity, and the gas compressibility coefficient;

[0098] S302: Constructing the water production prediction model according to the gas production prediction model, the water viscosity and the water compressibility coefficient.

[0099] It is understandable that the above step 3 is followed. Step 4: Collect the data: real-time gas production (Q g ), production pressure difference (ΔP=P e -P wf ), gas and water physical properties parameters Substitute the formation temperature (T) into the equivalent replacement formula to calculate the initial water production.

[0100] When performing step 4, the assumptions of the steady-state flow Darcy production equation are: (1) the flow direction is horizontal and the permeability of the formation is homogeneous K. (2) the gas reservoir has constant thickness h and is circular. (3) the gas is single-phase. (4) the flow is in the Darcy plane and radial. The seepage model is as follows: Figure 11 shown.

[0101] Darcy's law and gas flow equation:

[0102] For steady-state radial flow of gas, the integral form of Darcy's law is:

[0103]

[0104] Where P is the measured pressure of the production well, K is the permeability of the reservoir rock (unit: mD), h is the effective thickness of the reservoir, and P e represents the reservoir outer boundary pressure, P wf represents the bottom hole pressure, μ is the viscosity, is the average viscosity, is the mean value of compression coefficient, r e is the oil leakage radius, r w is the wellbore radius. Assuming the viscosity μ and gas deviation factor is the average value. After integration, we get:

[0105]

[0106] Gas volume coefficient and ground flow conversion:

[0107] Underground flow q res Need to convert to flow rate Q under ground standard conditions g Gas volume coefficient B g Defined as:

[0108]

[0109] Where T is the measured temperature of the production well, P sc is the pressure under standard conditions, T sc is the temperature under standard conditions, is the average pressure (usually taken as ). The surface flow rate is:

[0110]

[0111] Unit conversion and coefficient calculation:

[0112] Convert permeability K (mD), thickness h (ft), pressure (psi), temperature T (R), viscosity μ (cp) etc. into oilfield units to obtain the gas well productivity formula:

[0113]

[0114] The meaning of the symbols in the formula:

[0115] Among them, Q g represents the gas well productivity under standard conditions, K(mD) represents the permeability of the reservoir rock, h represents the effective thickness of the reservoir, P e represents the reservoir outer boundary pressure, P wf represents the bottom hole flowing pressure, T represents the reservoir temperature, represents the average viscosity of the gas, Represents the average deviation factor of the gas, r e Indicates the oil leakage radius, r w Represents the wellbore radius.

[0116] Unified form of seepage equation: Assuming that the single-phase seepage of gas and water under the same formation conditions follows a similar expression of Darcy's law, the model can be converted by simply adjusting the physical parameters.

[0117] Original gas well productivity equation:

[0118]

[0119] Water production equation after replacing water phase parameters:

[0120]

[0121] It can be seen from the above description that the method for determining the water production of ultra-deep gas wells provided in this application can construct a water production prediction model.

[0122] In one embodiment, see Figure 4, the use of the water production correction factor to correct the initial prediction value to obtain a final prediction value of water production includes:

[0123] S401: Establishing a proportional relationship between water production and gas production;

[0124] S402: Obtaining a conversion value of gas production according to the initial prediction value and the proportional relationship;

[0125] S403: Determine the product of the converted value of the gas production and the water production correction factor as the final predicted value.

[0126] It is understandable that the above step 4 is followed. Step 5: Adjust the correction factor according to the real-time pressure difference change, output the corrected water production forecast value, compare it with the measured water production data, and calibrate the model parameters (such as μ w , and f(ΔP)), and finally obtain the accurate water production prediction value.

[0127] By combining the gas and water flow equations, the proportional relationship between water production and gas production is established, eliminating the formation parameters (K, h, r e / r w ) redundant calculation:

[0128] according to get

[0129] Among them, μ g is the gas viscosity, is the mean value of the gas compressibility coefficient, μ w is the viscosity of water, is the mean value of water compressibility, Q w is the water production, Q g For gas production.

[0130] During step 5, because the production pressure difference will have a certain impact on the gas-water relative permeability, a correction factor (f(ΔP)) is introduced. It is defined by fitting historical production data or combining the gas-water relative permeability curve (using centrifugal force to change the fluid saturation in the core and calculating the relative permeability based on the relationship between centrifugal speed and fluid distribution):

[0131]

[0132] Among them, K rg is the relative permeability of gas, K rw is the relative permeability of water. If the correction factor f(ΔP)>1, it reflects the aggravation of water invasion; if f(ΔP)<1, it reflects the dominance of gas phase seepage.

[0133] Quantify the impact of changes in production pressure difference on the gas-water two-phase seepage ratio:

[0134]

[0135] Finally, the corrected theoretical drainage volume of the gas well is obtained.

[0136] From the above description, it can be seen that the method for determining the water production of ultra-deep gas wells provided in this application can use the water production correction factor to correct the initial prediction value to obtain the final prediction value of water production.

[0137] In order to better illustrate the method provided by this application, a specific example is given below.

[0138] In order to evaluate the production capacity of the K2 well (the production well section is located between 6805.00 and 6930.00 meters) and plan the subsequent conversion of the production well to a drainage well, it is necessary to calculate the drainage volume of the well to verify whether the drainage of the well is feasible. The implementation steps are as follows:

[0139] 1) To investigate the changes in the properties and phase characteristics of the reservoir fluid during production, two gas samples (2 x 20 L) were obtained from the separator after production stabilized and subjected to PVT analysis. The sampling conditions were: reservoir pressure of 93.63 MPa and reservoir temperature of 165.7°C. The sampling pressure was 11.38 MPa and the sampling temperature was 44.4°C.

[0140] 2) The PV relationship and gas deviation coefficient were measured under gas reservoir conditions, and the gas volume coefficient under gas reservoir conditions was obtained to be 2.5462×10 -3 m 3 / m 3 , gas viscosity is 3.548×10 -2 mPa·s. The PVT analysis research results data table (Table 1) is shown below.

[0141] Table 1 PVT analysis research results data table

[0142]

[0143] 3) The experimental data were normalized and the viscosity of water under formation conditions was found to be 0.97 mPa·s, and the compressibility of water was 0.5381 / MPa.

[0144] 4) The daily gas production of the well is 19.07 million cubic meters per day, the gas deviation coefficient under reservoir conditions is 1.5721, and the gas viscosity is 3.548×10 -2 mPa·s. The viscosity of water is 0.97 mPa·s, and the compressibility is 0.5381 / MPa.

[0145] Combine the gas and water flow equations to establish the proportional relationship between water production and gas production, and eliminate the formation parameters (K, h, r e / r w ) redundant calculation: The theoretical displacement is 160.4858 (cubic meters per day)

[0146] 5) From the gas-water relative permeability curve (K rg ,K rw ),get This indicates that the well is experiencing increased water intrusion. Introducing a correction factor increases the theoretical drainage rate, resulting in a drainage rate of 168.51 cubic meters per day. This drainage rate indicates that the well has strong drainage capacity and is suitable for conversion to a drainage well.

[0147] After conversion to a drainage well, the well's daily drainage rate was 170.48 cubic meters per day, with an error of less than 2% from the calculated theoretical drainage rate, demonstrating the feasibility and high accuracy of this method. As can be seen from the examples, the method for determining drainage rates in ultra-deep gas wells of the present invention has high accuracy and can provide a scientific basis for oil and gas field development planning.

[0148] Based on the same inventive concept, an embodiment of the present application also provides a device for determining the water production of an ultra-deep gas well, which can be used to implement the method described in the above embodiment, as described in the following embodiment. Since the principle of solving the problem by the device for determining the water production of an ultra-deep gas well is similar to the method for determining the water production of an ultra-deep gas well, the implementation of the device for determining the water production of an ultra-deep gas well can refer to the implementation of the method based on software performance benchmark determination, and the repeated parts will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceived.

[0149] In one embodiment, see Figure 5 In order to directly calculate the water production rate using only the gas production rate and the production pressure difference based on the gas well productivity equation by equivalently replacing the gas-water seepage parameters, the present application provides a device for determining the water production rate of an ultra-deep gas well, including: an initial prediction unit 501, a correction factor determination unit 502, and a final prediction unit 503.

[0150] The initial prediction unit 501 is used to input the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial prediction value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottom hole flowing pressure, gas and water physical properties and formation temperature;

[0151] The correction factor determination unit 502 is used to determine the water production correction factor according to the obtained gas-water relative permeability curve;

[0152] The final prediction unit 503 is configured to correct the initial prediction value using the water production correction factor to obtain a final prediction value of water production.

[0153] In one embodiment, see Figure 6 The gas and water physical property parameters include gas viscosity, gas compressibility coefficient, water viscosity and water compressibility coefficient; the initial prediction unit 501 includes: a gas sample and water sample acquisition module 601, a gas sample parameter determination module 602 and a water sample parameter determination module 603.

[0154] The gas and water sample acquisition module 601 is used to obtain gas and water samples from the gas reservoir of the ultra-deep gas well;

[0155] The gas sample parameter determination module 602 is used to perform pressure, volume, and temperature tests on the gas sample to obtain the gas viscosity and gas compressibility of the gas sample under gas reservoir conditions;

[0156] The water sample parameter determination module 603 is used to perform experimental analysis on the water sample to obtain the water viscosity and water compressibility under the formation temperature and production pressure difference conditions at the time of sampling.

[0157] In one embodiment, see Figure 7 The initial prediction unit 501 includes: a gas volume model generation module 701 and a water volume model generation module 702.

[0158] The gas production model generation module 701 is used to generate a gas production prediction model based on the permeability of the gas reservoir rock of the ultra-deep gas well, the effective reservoir thickness, the oil drainage radius, the wellbore radius, the reservoir outer boundary pressure, the bottom hole flowing pressure, the formation temperature, the gas viscosity and the gas compressibility coefficient;

[0159] The water production model generation module 702 is used to construct the water production prediction model according to the gas production prediction model, the water viscosity and the water compressibility coefficient.

[0160] In one embodiment, see Figure 8 The final prediction unit 503 includes: a proportional relationship establishment module 801, a converted gas volume determination module 802 and a final prediction module 803.

[0161] The proportional relationship establishing module 801 is used to establish the proportional relationship between water production and gas production;

[0162] A converted gas volume determination module 802 is configured to obtain a converted value of the gas production volume based on the initial predicted value and the proportional relationship;

[0163] The final prediction module 803 is configured to determine the product of the converted value of the gas production and the water production correction factor as the final prediction value.

[0164] From a hardware perspective, in order to directly calculate water production using only gas production and production pressure differential by equivalently replacing gas-water flow parameters based on the gas well productivity equation, the present application provides an embodiment of an electronic device for implementing all or part of the method for determining water production in an ultra-deep gas well. The electronic device specifically includes the following:

[0165] A processor, memory, a communications interface, and a bus; wherein the processor, memory, and communications interface communicate with each other via the bus; the communications interface is used to transmit information between the device for determining water production in an ultra-deep gas well and related devices such as a core business system, a user terminal, and a related database; the logic controller can be a desktop computer, a tablet computer, a mobile terminal, etc., but this embodiment is not limited thereto. In this embodiment, the logic controller can be implemented with reference to the embodiments of the method for determining water production in an ultra-deep gas well and the embodiments of the device for determining water production in an ultra-deep gas well, the contents of which are incorporated herein and repeated parts are not repeated.

[0166] It is understandable that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a personal digital assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Among them, the smart wearable device may include smart glasses, a smart watch, a smart bracelet, etc.

[0167] In practical applications, portions of the method for determining water production in ultra-deep gas wells can be executed on the electronic device as described above, or all operations can be performed on the client device. The specific selection can be based on the processing capabilities of the client device and the limitations of the user's usage scenario. This application does not impose any restrictions on this. If all operations are performed on the client device, the client device may also include a processor.

[0168] The client device may include a communication module (i.e., a communication unit) that can establish a communication connection with a remote server to implement data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0169] Figure 9 Schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Figure 9 As shown, the electronic device 9600 may include a central processing unit 9100 and a memory 9140; the memory 9140 is coupled to the central processing unit 9100. It is worth noting that the Figure 9 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0170] In one embodiment, the method for determining water production in ultra-deep gas wells may be integrated into the central processing unit 9100. The central processing unit 9100 may be configured to perform the following control:

[0171] S101: Inputting the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial predicted value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottom hole flowing pressure, gas and water physical properties, and formation temperature;

[0172] S102: determining a water production correction factor based on the obtained gas-water relative permeability curve;

[0173] S103: Correcting the initial prediction value using the water production correction factor to obtain a final prediction value of water production.

[0174] As can be seen from the above description, the method for determining water production in ultra-deep gas wells provided by this application can reflect the impact of changes in production pressure differential on water invasion in real time through a dynamic correction factor, and directly derive water production based on the gas-water seepage ratio, effectively overcoming the errors caused by static parameters or assumptions in traditional methods. It reduces dependence on data and simplifies parameter requirements. It only requires real-time gas production and production pressure differential data to achieve water production, without relying on a large amount of historical data. It directly uses known gas parameters for calculation through equivalent substitution theory, significantly reducing data acquisition cost and complexity. This calculation model can adapt to different water production sources (such as formation water, fracture inrush water) and dynamic water invasion conditions (such as after water plugging measures or water invasion intensification), breaking through the traditional empirical formula's reliance on a stable water-gas ratio, and is particularly suitable for the complex geological and development environments of ultra-deep gas wells. By transforming the gas well productivity equation, it incorporates gas and water production into a unified seepage framework, avoiding the redundant process of independent calculations of multiple models. On-site prediction results can be quickly output by simply calibrating the correction factors based on real-time data, reducing the need for complex experiments (such as high-frequency water phase physical property testing) and dedicated software.

[0175] In another embodiment, the device for determining the water production of ultra-deep gas wells can be configured separately from the central processor 9100. For example, the data composite transmission device for determining the water production of ultra-deep gas wells can be configured as a chip connected to the central processor 9100, and the function of the method for determining the water production of ultra-deep gas wells can be realized through the control of the central processor.

[0176] like Figure 9 As shown, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Figure 9 In addition, the electronic device 9600 may also include all components shown in Figure 9 For components not shown, reference may be made to the prior art.

[0177] like Figure 9 As shown, the central processing unit 9100 is sometimes also referred to as a controller or operation control, and may include a microprocessor or other processor device and / or logic device. The central processing unit 9100 receives input and controls the operation of various components of the electronic device 9600.

[0178] Memory 9140 can be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It can store the aforementioned failure-related information and also store programs that execute the relevant information. The CPU 9100 can execute the programs stored in memory 9140 to implement information storage or processing.

[0179] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 may be, for example, a keypad or touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display objects such as images and text. The display may be, for example, an LCD display, but is not limited thereto.

[0180] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), or a SIM card. Alternatively, it may be a memory that retains information even when power is off, can be selectively erased, and is provided with more data. Examples of such memory are sometimes referred to as EPROMs. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142 for storing application programs and function programs or processes for executing the operation of the electronic device 9600 by the central processing unit 9100.

[0181] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various driver programs for the electronic device's communication functions and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0182] The communication module 9110 is a transmitter / receiver that sends and receives signals via the antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in a conventional mobile communication terminal.

[0183] Based on different communication technologies, multiple communication modules 9110 can be provided in the same electronic device, such as a cellular network module, a Bluetooth module, and / or a wireless local area network module. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing common telecommunication functions. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processing unit 9100, enabling local recording via the microphone 9132 and playback of stored audio via the speaker 9131.

[0184] Embodiments of the present application also provide a computer-readable storage medium capable of implementing all steps of the method for determining water production in an ultra-deep gas well in the above-mentioned embodiment, where the execution subject is a server or a client. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all steps of the method for determining water production in an ultra-deep gas well in the above-mentioned embodiment, where the execution subject is a server or a client, are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0185] S101: Inputting the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial predicted value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottom hole flowing pressure, gas and water physical properties, and formation temperature;

[0186] S102: determining a water production correction factor based on the obtained gas-water relative permeability curve;

[0187] S103: Correcting the initial prediction value using the water production correction factor to obtain a final prediction value of water production.

[0188] As can be seen from the above description, the method for determining water production in ultra-deep gas wells provided by this application can reflect the impact of changes in production pressure differential on water invasion in real time through a dynamic correction factor, and directly derive water production based on the gas-water seepage ratio, effectively overcoming the errors caused by static parameters or assumptions in traditional methods. It reduces dependence on data and simplifies parameter requirements. It only requires real-time gas production and production pressure differential data to achieve water production, without relying on a large amount of historical data. It directly uses known gas parameters for calculation through equivalent substitution theory, significantly reducing data acquisition cost and complexity. This calculation model can adapt to different water production sources (such as formation water, fracture inrush water) and dynamic water invasion conditions (such as after water plugging measures or water invasion intensification), breaking through the traditional empirical formula's reliance on a stable water-gas ratio, and is particularly suitable for the complex geological and development environments of ultra-deep gas wells. By transforming the gas well productivity equation, it incorporates gas and water production into a unified seepage framework, avoiding the redundant process of independent calculations of multiple models. On-site prediction results can be quickly output by simply calibrating the correction factors based on real-time data, reducing the need for complex experiments (such as high-frequency water phase physical property testing) and dedicated software.

[0189] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatus, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0190] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as a combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0191] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0192] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0193] Specific embodiments are used in the present invention to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A method for determining water production in an ultra-deep gas well, characterized in that: include: Inputting the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial predicted value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottomhole flowing pressure, gas and water physical properties and formation temperature; Determine the water production correction factor based on the obtained gas-water relative permeability curve; The initial predicted value is corrected using the water production correction factor to obtain a final predicted value of water production.

2. The method for determining water production of an ultra-deep gas well according to claim 1, wherein: The gas and water physical parameters include gas viscosity, gas compressibility, water viscosity and water compressibility; The step of obtaining the environmental parameters of the ultra-deep gas well includes: Obtain gas and water samples from ultra-deep gas well reservoirs; Performing pressure, volume, and temperature tests on the gas sample to obtain the gas viscosity and gas compressibility of the gas sample under gas reservoir conditions; The water samples are subjected to experimental analysis to obtain the water viscosity and water compressibility coefficient under the formation temperature and production pressure differential conditions at the time of sampling.

3. The method for determining water production of an ultra-deep gas well according to claim 2, wherein: The step of pre-building the water production prediction model includes: Generate a gas production prediction model based on the permeability of the gas reservoir rock of the ultra-deep gas well, the effective thickness of the reservoir, the oil drainage radius, the wellbore radius, the outer boundary pressure of the reservoir, the bottom hole flowing pressure, the formation temperature, the gas viscosity and the gas compressibility coefficient; The water production prediction model is constructed according to the gas production prediction model, the water viscosity and the water compressibility coefficient.

4. The method for determining water production of an ultra-deep gas well according to claim 1, wherein: The method of correcting the initial predicted value by using the water production correction factor to obtain a final predicted value of water production includes: Establish the proportional relationship between water production and gas production; Obtaining a conversion value of gas production according to the initial predicted value and the proportional relationship; The product of the converted value of the gas production and the water production correction factor is determined as the final predicted value.

5. A device for determining water production in ultra-deep gas wells, characterized in that: include: An initial prediction unit is used to input the acquired ultra-deep gas well environmental parameters into a pre-built water production prediction model to obtain an initial predicted value of water production; wherein the gas well environmental parameters include real-time gas production, reservoir outer boundary pressure, bottom hole flowing pressure, gas and water physical properties and formation temperature; A correction factor determination unit, used to determine a water production correction factor based on the obtained gas-water relative permeability curve; The final prediction unit is used to correct the initial prediction value using the water production correction factor to obtain a final prediction value of the water production.

6. The device for determining water production of ultra-deep gas wells according to claim 5, characterized in that: The gas and water physical parameters include gas viscosity, gas compressibility, water viscosity and water compressibility; The initial prediction unit includes: Gas and water sample acquisition module, used to obtain gas and water samples from ultra-deep gas well reservoirs; A gas sample parameter determination module is used to perform pressure, volume, and temperature tests on the gas sample to obtain the gas viscosity and gas compressibility of the gas sample under gas reservoir conditions; The water sample parameter determination module is used to perform experimental analysis on the water sample to obtain the water viscosity and water compressibility coefficient under the formation temperature and production pressure difference conditions at the time of sampling.

7. The device for determining water production of ultra-deep gas wells according to claim 6, characterized in that: The initial prediction unit includes: A gas production model generation module is used to generate a gas production prediction model based on the permeability of the gas reservoir rock of the ultra-deep gas well, the effective thickness of the reservoir, the oil drainage radius, the wellbore radius, the outer boundary pressure of the reservoir, the bottom hole flowing pressure, the formation temperature, the gas viscosity and the gas compressibility coefficient; The water production model generation module is used to construct the water production prediction model according to the gas production prediction model, the water viscosity and the water compressibility coefficient.

8. The device for determining water production of ultra-deep gas wells according to claim 5, characterized in that: The final prediction unit includes: A proportional relationship establishment module is used to establish the proportional relationship between water production and gas production; A converted gas volume determination module, configured to obtain a converted value of the gas production volume based on the initial predicted value and the proportional relationship; The final prediction module is used to determine the product of the converted value of the gas production and the water production correction factor as the final prediction value.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for determining water production in an ultra-deep gas well according to any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for determining water production in an ultra-deep gas well according to any one of claims 1 to 4 are implemented.

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