A method and apparatus for optimizing the injection of carbon dioxide mixed with nitrogen

Abstract

The application discloses a kind of carbon dioxide and nitrogen mixed injection optimization method and device, comprising: various gas mixed ratio combination is input to the target three-dimensional geological model of oil and gas reservoir, according to the first simulation result output, from various gas mixed ratio combination, select the target gas mixed ratio combination theoretically feasible;Target gas mixed ratio combination is input to the target three-dimensional geological model of oil and gas reservoir, according to the second simulation result output, from target gas mixed ratio combination, select the first target gas mixed ratio combination actually feasible;According to the first target gas mixed ratio combination, select gas mixed ratio combination to form target gas mixture;From target position, obtain oil and gas reservoir monitoring data and compare with second simulation result, according to the comparison result adjustment gas mixed ratio combination, to optimize actual injection effect.The application can dynamically, accurately adjust gas mixed ratio, significantly improve oil and gas recovery, reduce overall injection cost.

Description

Technical Field

[0001] This invention relates to the field of oil and gas extraction technology, and in particular to an optimized method and apparatus for injecting a mixture of carbon dioxide and nitrogen. Background Technology

[0002] In the field of oil and gas extraction, traditional gas injection methods include carbon dioxide injection and nitrogen injection. Carbon dioxide injection can significantly improve oil and gas recovery rates, but it is costly and technically complex. While nitrogen injection has a lower cost, its effect on improving recovery rates is usually not as significant as that of carbon dioxide injection. Using either carbon dioxide or nitrogen injection alone often makes it difficult to achieve an ideal balance between cost and recovery rate.

[0003] Existing technologies cannot dynamically and accurately optimize or adjust the mixing ratio of carbon dioxide and nitrogen by monitoring oil and gas reservoir data in real time. As a result, they cannot adapt to the characteristics and needs of different oil and gas reservoirs, leading to low oil and gas recovery rates, high overall injection costs, and poor actual injection effects.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This specification provides an optimized method and apparatus for injecting carbon dioxide and nitrogen mixtures to address the problems of existing technologies being unable to dynamically and accurately optimize or adjust the mixing ratio of carbon dioxide and nitrogen, thus failing to adapt to the characteristics and needs of different oil and gas reservoirs, resulting in low oil and gas recovery rates, high overall injection costs, and poor actual injection effects.

[0006] Firstly, embodiments of this specification provide an optimized method for injecting a mixture of carbon dioxide and nitrogen, including:

[0007] Various gas mixing ratio combinations are input into the target three-dimensional geological model of the oil and gas reservoir. Based on the first simulation result output, a theoretically feasible target gas mixing ratio combination is selected from various gas mixing ratio combinations.

[0008] The target gas mixing ratio combination is input into the target three-dimensional geological model of the oil and gas reservoir. Based on the output of the second simulation results, the first feasible target gas mixing ratio combination is selected from the target gas mixing ratio combinations.

[0009] Based on the first target gas mixing ratio combination, a gas mixing ratio combination is selected to form a target gas mixture, which is used to be injected into the target location of the oil and gas reservoir;

[0010] Oil and gas reservoir monitoring data are obtained from the target location and compared with the results of the second simulation. The gas mixing ratio is adjusted according to the comparison results to optimize the actual injection effect.

[0011] In some embodiments, the method further includes:

[0012] The oil and gas reservoir area is divided into a predetermined number of grid cells, and the collected geological data is distributed to each grid cell through interpolation to create an initial three-dimensional geological model of the oil and gas reservoir. The predetermined number is determined based on the total volume of the oil and gas reservoir and the volume of each grid cell.

[0013] Fluid properties and fluid flow behavior are modeled, and the modeling results of fluid properties and the simulation results of fluid flow are coupled into the initial three-dimensional geological model of the oil and gas reservoir to obtain the three-dimensional geological model of the oil and gas reservoir. The fluid properties include fluid density and fluid viscosity, and the fluid flow behavior includes fluid flow rate.

[0014] The three-dimensional geological model of the oil and gas reservoir is validated. When the validation is successful, the target three-dimensional geological model of the oil and gas reservoir is obtained.

[0015] In some embodiments, inputting various gas mixing ratios into the target three-dimensional geological model of the oil and gas reservoir includes:

[0016] Various gas mixing ratios are input into the target three-dimensional geological model of the oil and gas reservoir to determine the first total recovery rate corresponding to the various gas mixing ratios and output the first simulation result, which includes the first total recovery rate prediction data.

[0017] Accordingly, selecting a theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations based on the output of the first simulation result includes:

[0018] By comparing the first total recovery rate prediction data corresponding to various gas mixing ratio combinations, a target gas mixing ratio combination in which the first total recovery rate prediction data is greater than a first preset threshold is selected from various gas mixing ratio combinations as a theoretically feasible target gas mixing ratio combination.

[0019] In some embodiments, determining the first overall recovery rate corresponding to various gas mixing ratio combinations includes:

[0020] The pressure drop during the injection of each grid cell is determined based on various gas mixing ratios.

[0021] Based on the pressure drop, determine the fluid flow behavior of each grid cell;

[0022] The recovery rate of each grid cell is determined based on the fluid flow behavior.

[0023] The recovery rates of each grid cell are summed to obtain the first total recovery rate corresponding to various gas mixing ratio combinations.

[0024] In some embodiments, inputting the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir includes:

[0025] The target gas mixing ratio combination is input into the target three-dimensional geological model of the oil and gas reservoir to determine the second total recovery rate corresponding to the target gas mixing ratio combination and output the second simulation result, which includes the second total recovery rate prediction data.

[0026] Accordingly, selecting a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations based on the output second simulation result includes:

[0027] By comparing the second total recovery rate prediction data corresponding to the target gas mixing ratio combination, a first target gas mixing ratio combination in which the second total recovery rate prediction data is greater than a second preset threshold is selected from the target gas mixing ratio combinations as the actually feasible first target gas mixing ratio combination, wherein the second preset threshold is greater than the first preset threshold.

[0028] In some embodiments, determining the second total recovery rate corresponding to the target gas mixing ratio combination includes:

[0029] The second total recovery rate is determined using the following formula:

[0030]

[0031] Among them, R total_2 φ(x,y,z) represents the second overall recovery rate; φ(x,y,z) represents the porosity distribution function; S(x,y,z) represents the crude oil saturation distribution function. This refers to the multi-physics coupling effect in the gas-fuel displacement process. This refers to the mixing ratio of carbon dioxide; κ represents the nitrogen mixing ratio; Q represents the injection flow rate in the injection parameters; P represents the formation pressure; T represents the formation temperature; and κ represents the reservoir permeability.

[0032] In some embodiments, selecting a gas mixing ratio combination based on a first target gas mixing ratio combination includes:

[0033] The first target gas mixing ratio combination is used as the target value, and the current gas mixing ratio combination is adjusted once until the first error value between the first target gas mixing ratio combination and the adjusted gas mixing ratio combination is less than the first preset error threshold.

[0034] The adjusted gas mixing ratio combination is used as the selected gas mixing ratio combination.

[0035] In some embodiments, the step of comparing the oil and gas reservoir monitoring data obtained from the target location with the second simulation results, and adjusting the gas mixing ratio combination according to the comparison results, includes:

[0036] Calculate the second error value between the oil and gas reservoir monitoring data and the second simulation results;

[0037] Based on the second error value, determine the adjustment amount for the secondary adjustment of the gas mixing ratio combination;

[0038] Based on the adjustment amount and oil and gas reservoir monitoring data, the gas mixing ratio combination is adjusted a second time to obtain the gas mixing ratio combination after the second adjustment.

[0039] Secondly, embodiments of this specification also provide a carbon dioxide and nitrogen gas mixing and injection optimization device, comprising:

[0040] The first selection module is used to input various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, and select the theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations based on the output first simulation results.

[0041] The second selection module is used to input the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir, and select the first feasible target gas mixing ratio combination from the target gas mixing ratio combination based on the output second simulation results.

[0042] A mixing module is used to select a gas mixing ratio combination to form a target gas mixture based on a first target gas mixing ratio combination, the target gas mixture being injected at a target location in an oil and gas reservoir.

[0043] The optimization module is used to acquire oil and gas reservoir monitoring data from the target location and compare it with the second simulation results. Based on the comparison results, the gas mixing ratio is adjusted to optimize the actual injection effect.

[0044] Thirdly, embodiments of this specification also provide a computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the steps of the above-described optimized method for injecting a mixture of carbon dioxide and nitrogen.

[0045] This specification provides a method and apparatus for optimizing the injection of carbon dioxide and nitrogen mixtures. First, various gas mixing ratios can be input into a target three-dimensional geological model of an oil and gas reservoir. Based on the output of a first simulation result, a theoretically feasible target gas mixing ratio combination is selected from the various gas mixing ratio combinations. Then, the target gas mixing ratio combination is input into the target three-dimensional geological model of the oil and gas reservoir. Based on the output of a second simulation result, a practically feasible first target gas mixing ratio combination is selected from the target gas mixing ratio combinations. Next, based on the first target gas mixing ratio combination, a gas mixing ratio combination is selected to form a target gas mixture, which is used for injection at the target location of the oil and gas reservoir. Finally, oil and gas reservoir monitoring data is obtained from the target location and compared with the second simulation result. Based on the comparison result, the gas mixing ratio combination is adjusted to optimize the actual injection effect. In this specification embodiment, by inputting various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, detailed simulation can be performed using the target three-dimensional geological model to accurately obtain the first simulation result (e.g., first total recovery rate prediction data). Through simulation analysis, a theoretically feasible target gas mixing ratio combination can be accurately found. By inputting the target gas mixing ratio into the target 3D geological model of the oil and gas reservoir, a second simulation result (such as second total oil recovery prediction data) can be accurately obtained. Through simulation analysis, a practically feasible first target gas mixing ratio can be accurately found from the theoretically feasible target gas mixing ratio combinations. Based on the practically feasible first target gas mixing ratio, the gas mixing ratio combination can be accurately selected to form the target gas mixture. Injecting the target gas mixture into the target location of the oil and gas reservoir and obtaining reservoir monitoring data, which is then compared with the second simulation result, allows for dynamic and accurate adjustment of the gas mixing ratio combination during the actual injection process. This optimizes the actual injection effect, significantly improves oil and gas recovery, and reduces overall injection costs. Furthermore, adjusting the gas mixing ratio combination based on real-time reservoir monitoring data better adapts to the characteristics and needs of different oil and gas reservoirs. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0047] Figure 1 This is a schematic flowchart of an optimized method for injecting a mixture of carbon dioxide and nitrogen provided in the embodiments of this specification;

[0048] Figure 2This is a schematic diagram illustrating an embodiment of an optimized method for injecting carbon dioxide and nitrogen mixtures provided in this specification, applied in a scenario example.

[0049] Figure 3 This is a schematic diagram illustrating an embodiment of an optimized method for injecting carbon dioxide and nitrogen mixtures provided in this specification, applied in a scenario example.

[0050] Figure 4 This is a schematic diagram illustrating an embodiment of an optimized method for injecting carbon dioxide and nitrogen mixtures provided in this specification, applied in a scenario example.

[0051] Figure 5 This is a schematic diagram of the structural composition of an optimized device for mixing and injecting carbon dioxide and nitrogen, as provided in the embodiments of this specification.

[0052] Figure 6 This is a schematic diagram of the structural composition of the electronic device provided in the embodiments of this specification. Detailed Implementation

[0053] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0054] As mentioned above, in the field of oil and gas extraction, traditional gas injection methods include carbon dioxide injection and nitrogen injection. Carbon dioxide injection can significantly improve oil and gas recovery, but it is costly and technically complex. While nitrogen injection has a lower cost, its effect on improving recovery is generally not as significant as that of carbon dioxide injection. Using carbon dioxide injection or nitrogen injection alone often makes it difficult to achieve an ideal balance between cost and recovery.

[0055] Existing technologies cannot optimize the mixing of carbon dioxide and nitrogen, nor can they dynamically and accurately adjust the mixing ratio of gas mixtures by monitoring oil and gas reservoir data in real time. As a result, they cannot better adapt to the characteristics and needs of different oil and gas reservoirs, and cannot achieve a significant improvement in recovery rate while maintaining economic efficiency.

[0056] To address the aforementioned problems, this specification provides a method and apparatus for optimizing the injection of carbon dioxide and nitrogen mixtures. First, various gas mixing ratios can be input into a target three-dimensional geological model of the oil and gas reservoir. Based on the output of a first simulation result, a theoretically feasible target gas mixing ratio combination is selected from these combinations. Then, the target gas mixing ratio combination is input into the target three-dimensional geological model of the oil and gas reservoir. Based on the output of a second simulation result, a practically feasible first target gas mixing ratio combination is selected from the target gas mixing ratio combinations. Next, based on the first target gas mixing ratio combination, a gas mixing ratio combination is selected to form a target gas mixture, which is used for injection at the target location of the oil and gas reservoir. Finally, oil and gas reservoir monitoring data is obtained from the target location and compared with the second simulation result. Based on the comparison result, the gas mixing ratio combination is adjusted to optimize the actual injection effect.

[0057] The above-described scheme maximizes oil and gas recovery within an economically acceptable range. This method combines the advantages of two gases and adjusts the gas mixing ratio based on reservoir monitoring data and simulation results from the target 3D geological model. This better adapts to the characteristics and needs of different oil and gas reservoirs, avoiding the high cost and low recovery rate problems associated with single-gas injection, thus achieving an optimal balance between improved recovery and cost-effectiveness.

[0058] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate for the embodiments of this application described herein.

[0059] It is understood that the methods described in the embodiments of this specification can be applied to electronic devices, which can refer to electronic devices with data computing, processing, and storage capabilities. These electronic devices can be terminals such as PCs (Personal Computers), tablets, smartphones, wearable devices, and intelligent robots; they can also be servers. A server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0060] See Figure 1 As shown in the embodiments of this specification, an optimized method for injecting a mixture of carbon dioxide and nitrogen is provided. In specific implementation, this method may include the following:

[0061] S101: Input various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, and select the theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations based on the output first simulation results;

[0062] S102: Input the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir, and select the first feasible target gas mixing ratio combination from the target gas mixing ratio combinations based on the output second simulation results;

[0063] S103: Based on the first target gas mixing ratio combination, select a gas mixing ratio combination to form a target gas mixture, the target gas mixture being injected into the target location of the oil and gas reservoir;

[0064] S104: Obtain oil and gas reservoir monitoring data from the target location and compare it with the second simulation results. Adjust the gas mixing ratio combination according to the comparison results to optimize the actual injection effect.

[0065] Based on the above embodiments, by inputting various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, detailed simulations can be performed using the target three-dimensional geological model to accurately obtain the first simulation result (e.g., first total recovery rate prediction data). Through simulation analysis, theoretically feasible target gas mixing ratio combinations can be accurately identified. By inputting the target gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, second simulation results (e.g., second total recovery rate prediction data) can be accurately obtained. Through simulation analysis, practically feasible first target gas mixing ratio combinations can be accurately identified from the theoretically feasible target gas mixing ratio combinations. Based on the practically feasible first target gas mixing ratio combinations, the gas mixing ratio combination can be accurately selected to form the target gas mixture. Injecting the target gas mixture into the target location of the oil and gas reservoir, obtaining reservoir monitoring data, and comparing it with the second simulation results allows for dynamic and accurate adjustment of the gas mixing ratio combination during the actual injection process. This optimizes the actual injection effect, significantly improves oil and gas recovery rate, and reduces overall injection costs. Furthermore, adjusting the gas mixing ratio combination based on real-time reservoir monitoring data can better adapt to the characteristics and needs of different oil and gas reservoirs.

[0066] In some embodiments, prior to S101 above, the following may also be included:

[0067] The oil and gas reservoir area is divided into a predetermined number of grid cells, and the collected geological data is distributed to each grid cell through interpolation to create an initial three-dimensional geological model of the oil and gas reservoir. The predetermined number is determined based on the total volume of the oil and gas reservoir and the volume of each grid cell.

[0068] Fluid properties and fluid flow behavior are modeled, and the modeling results of fluid properties and the simulation results of fluid flow are coupled into the initial three-dimensional geological model of the oil and gas reservoir to obtain the three-dimensional geological model of the oil and gas reservoir. The fluid properties include fluid density and fluid viscosity, and the fluid flow behavior includes fluid flow rate.

[0069] The three-dimensional geological model of the oil and gas reservoir is validated. When the validation is successful, the target three-dimensional geological model of the oil and gas reservoir is obtained.

[0070] Specifically, the aforementioned preset quantities are determined based on the total volume of the oil and gas reservoir and the volume of each grid cell, and may include:

[0071] Determine the preset quantity using the following formula:

[0072]

[0073] Where, N grid The preset quantity (i.e., the total number of grid cells); V reservoir V represents the total volume of the oil and gas reservoir. cell This represents the volume of each grid cell.

[0074] The geological data collected may include, but is not limited to, porosity, permeability (reservoir permeability), formation pressure, and formation temperature. The collected geological data will be distributed to individual grid cells through interpolation, and may include:

[0075] Using inverse distance weighted interpolation, porosity and permeability interpolation values ​​are assigned to each grid cell according to the following formula:

[0076]

[0077] Where f(x) represents the attribute value of the target point; f i The values ​​of the known data points; d i is the distance between the target point and the known points; p is the weighting exponent. It should be noted that the target point is the center point of the grid cell from which the attribute value (e.g., porosity or permeability) needs to be calculated, and the known data points are the known porosity or permeability values.

[0078] The relationship between porosity and permeability is as follows:

[0079] k=k0·Φ A

[0080] Where k is the permeability; k0 is the initial permeability; Φ is the porosity; and A is an empirical coefficient.

[0081] The formation pressure and formation temperature are interpolated and distributed to each grid cell according to the following formula:

[0082]

[0083] Where P(x,y) is the pressure value of the target point; P1 and P2 are the pressure values ​​of the known points; and x1 and x2 are the coordinates of the known points.

[0084] The fluid properties mentioned above can include fluid density and fluid viscosity, and the modeling of these fluid properties can include:

[0085] Model fluid properties using the following formula:

[0086] The fluid density modeling process is as follows:

[0087]

[0088] Where ρ is the fluid density; ρ0 is the density under standard conditions; B oi B is the volume coefficient of oil; wi is the volume coefficient of water.

[0089] The fluid viscosity modeling process is as follows:

[0090]

[0091] Where μ is the fluid viscosity; μ0 is the viscosity at the reference temperature; T0 is the reference temperature; T is the actual temperature; and a0 is the temperature index.

[0092] The above modeling of fluid flow behavior can include:

[0093] Model fluid flow behavior using the following formula (Darcy's law, applicable to single-phase flow):

[0094]

[0095] Where Q is the fluid flow rate (or Darcy flow rate); k is the permeability; A is the flow area; ΔP is the pressure difference; μ is the fluid viscosity; and L is the flow path length.

[0096] For more complex flow conditions, relative permeability and capillary pressure can be introduced, and the multiphase flow equations can be solved using numerical methods (finite difference / finite volume). This specification does not make specific limitations on this.

[0097] The fluid property modeling results and fluid flow simulation results mentioned above can be coupled into the initial three-dimensional geological model of the oil and gas reservoir to obtain the three-dimensional geological model of the oil and gas reservoir.

[0098] Among these, fluid property modeling results (fluid density and fluid viscosity) directly affect fluid flow behavior and pressure distribution, forming the basis for dynamic simulations in 3D geological models. Fluid flow simulation results (fluid flow behavior, i.e., fluid flow rate) are the core formula connecting fluid properties and recovery rate prediction. Various gas mixing ratios can be input into the 3D geological model, and by calculating fluid properties and fluid flow behavior, recovery rate changes under different injection conditions can be accurately predicted.

[0099] Afterwards, the three-dimensional geological model of the oil and gas reservoir can be validated, for example, by using root mean square error (RMSE) or mean absolute error (MAE) to assess the model's predictive accuracy.

[0100]

[0101] Among them, y i These are actual measured values; is the model's predicted value, and n is the number of data points.

[0102] When the verification passes (i.e., the calculated root mean square error (RMSE) or mean absolute error (MAE) is less than the preset error threshold), the 3D geological model of the oil and gas reservoir can be used as the target 3D geological model for the reservoir. When the verification fails (i.e., the calculated RMSE or MAE is greater than the preset error threshold), the least squares method can be used to optimize the model parameters so that the optimized 3D geological model's RMSE or MAE is less than the preset error threshold. In this case, the optimized 3D geological model of the oil and gas reservoir can be used as the target 3D geological model for the reservoir. The preset error threshold can be set according to actual needs; this specification does not specify a particular threshold. The target 3D geological model of the oil and gas reservoir may include porosity, permeability, fluid properties, etc., to accurately predict recovery rate changes under different injection conditions. The formula for optimizing model parameters using the least squares method is as follows:

[0103]

[0104] Where "minimize" means to minimize the objective function, such that y i as close as possible This minimizes the error in the model's predictions (i.e., it is less than a preset error threshold); y i These are actual measured values; is the model's predicted value, and n is the number of data points.

[0105] By validating the three-dimensional geological model of the oil and gas reservoir, it can be ensured that the validated three-dimensional geological model can accurately predict the changes in recovery rate under different injection conditions (such as different gas mixing ratios).

[0106] In some embodiments, inputting the various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir in S101 above may, in specific implementation, include:

[0107] Various gas mixing ratios are input into the target three-dimensional geological model of the oil and gas reservoir to determine the first total recovery rate corresponding to the various gas mixing ratios and output the first simulation result, which includes the first total recovery rate prediction data.

[0108] Accordingly, the above-mentioned selection of a theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations based on the first simulation result can, in specific implementation, include:

[0109] By comparing the first total recovery rate prediction data corresponding to various gas mixing ratio combinations, a target gas mixing ratio combination in which the first total recovery rate prediction data is greater than a first preset threshold is selected from various gas mixing ratio combinations as a theoretically feasible target gas mixing ratio combination.

[0110] Specifically, the aforementioned combinations of gas mixing ratios can include combinations of various gas mixing ratios, such as combinations of various carbon dioxide and nitrogen mixing ratios, and can also include corresponding injection parameters (such as injection rate (or injection flow rate), injection pressure, etc.). The combinations of various carbon dioxide and nitrogen mixing ratios can include, but are not limited to, combinations of 0-100% carbon dioxide gas and 0-100% nitrogen gas to cover a variety of possible injection schemes. The carbon dioxide mixing ratio can be determined according to the following formula:

[0111]

[0112] in, This refers to the mixing ratio of carbon dioxide; This represents the volume of carbon dioxide. This represents the volume of nitrogen gas. This formula calculates the proportion of carbon dioxide in the gas mixture.

[0113] The mixing ratio of nitrogen can be determined according to the following formula:

[0114]

[0115] in, This refers to the mixing ratio of nitrogen. By adjusting... and The value can be set to combine various gas mixing ratios, from pure carbon dioxide to pure nitrogen.

[0116] The combination of various gas mixing ratios (simulation scheme, i.e., representing all possible combinations of gas mixing ratios) can be expressed by the following formula:

[0117]

[0118] The above-mentioned input of various gas mixing ratio combinations into the target 3D geological model of the oil and gas reservoir is equivalent to setting various gas mixing ratio combinations and corresponding injection parameters in the target 3D geological model of the oil and gas reservoir, running simulation analysis to calculate the first total recovery rate (the first total recovery rate can be understood as the theoretical total recovery rate of the reservoir area) under each gas mixing ratio combination and corresponding injection parameters, and generating and outputting the first total recovery rate prediction data. The first total recovery rate prediction data can be compared to select the theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations, that is, select the theoretically optimal target gas mixing ratio combination and corresponding injection parameters. If the first total recovery rate prediction data corresponding to the target gas mixing ratio combination (or the first total recovery rate prediction data under the target gas mixing ratio combination) is greater than a first preset threshold, then the first total recovery rate prediction data corresponding to the target gas mixing ratio combination is theoretically optimal. The first preset threshold can be set according to actual needs, and this specification does not specifically limit it.

[0119] In some embodiments, the determination of the first overall recovery rate corresponding to various gas mixing ratio combinations described above may, in specific implementation, include:

[0120] The pressure drop during the injection of each grid cell is determined based on various gas mixing ratios.

[0121] Based on the pressure drop, determine the fluid flow behavior of each grid cell;

[0122] The recovery rate of each grid cell is determined based on the fluid flow behavior.

[0123] The recovery rates of each grid cell are summed to obtain the first total recovery rate corresponding to various gas mixing ratio combinations.

[0124] Specifically, the pressure drop determined during the injection of various grid cells based on the above-mentioned combinations of gas mixing ratios can include:

[0125] The density of the mixed gas is determined according to the following formula based on the various gas mixing ratios:

[0126]

[0127] Where, ρmix The density of the mixed gas; The density of carbon dioxide; The density of nitrogen gas; This refers to the mixing ratio of carbon dioxide; This refers to the mixing ratio of nitrogen gas.

[0128] Based on the various gas mixing ratios, the viscosity of the gas mixture is determined using the following formula:

[0129]

[0130] Where, μ mix The viscosity of the mixed gas; The viscosity of carbon dioxide; The viscosity of nitrogen gas is given.

[0131] Viscosity directly affects the flow resistance of gas, thus affecting the efficiency of the injection process.

[0132] Based on the various gas mixing ratios, the flow rate of the mixed gas is determined according to the following formula:

[0133]

[0134] Among them, Q mix This refers to the flow rate of the mixed gas; The flow rate of carbon dioxide; This represents the flow rate of nitrogen gas.

[0135] All of these were obtained through experiments, and this manual will not elaborate on them further.

[0136] Based on the viscosity and flow rate of the mixed gas, the possible pressure drop during the injection process (i.e., the pressure drop during the injection of each grid cell) is determined according to the following formula:

[0137]

[0138] Wherein, ΔP i Q represents the pressure drop during the injection of each grid cell. mix The flow rate of the mixed gas; μ mix denoted as ρ, where L is the viscosity of the mixed gas; L is the flow path length; A is the flow area; and k is the reservoir permeability.

[0139] The determination of fluid flow behavior in each grid cell based on pressure drop can include:

[0140] The fluid flow behavior of each grid cell is determined using the following formula:

[0141]

[0142] Among them, Q i The fluid flow rate (m³) of each grid cell 3 / s); k is the permeability (m 2 A is the flow area (m²) 2 );ΔP i denoted as pressure drop (Pa) during injection into each grid cell; μ as fluid viscosity (Pa·s); and L as flow path length (m).

[0143] The above-mentioned determination of the recovery rate of each grid cell based on fluid flow behavior may include:

[0144] The recovery rate of each grid cell is determined using the following formula:

[0145]

[0146] Among them, R i Let Q be the recovery rate of the i-th grid cell; prod,i The production flow rate (m) of the i-th grid cell 3 );S i The initial storage (m) of the i-th grid cell 3 ).

[0147] The recovery rates of each grid cell can be summed using the following formula to obtain the first overall recovery rate corresponding to various gas mixing ratio combinations:

[0148]

[0149] Among them, R total_1 B represents the first total recovery rate; B represents the number of regions.

[0150] Oil and gas reservoirs are typically divided into multiple grid cells, each with potentially different fluid properties and injection effects. Therefore, the recovery rate of each grid cell can be predicted, and these predictions can be summed to obtain the initial total recovery rate (TTR). By adjusting the combination of various gas mixing ratios and corresponding injection parameters, the TTR can be optimized. total_1 Theoretically, it can reach its maximum or optimal state.

[0151] In some embodiments, various gas mixing ratio combinations can be input into the target three-dimensional geological model of the oil and gas reservoir, and simulation analysis can be run to evaluate the impact of different mixing ratios and injection parameters on the recovery rate, determine the theoretically optimal gas mixing ratio combination and injection parameters, and improve the actual injection effect based on this.

[0152] To quickly select a theoretically feasible target gas mixing ratio from various gas mixing ratio combinations, an objective function can be set before running the simulation analysis:

[0153]

[0154] When running the simulation analysis, you can first iterate through various gas mixing ratio combinations and calculate Q sequentially. i R i R total_1 .

[0155] Then, the gradient of the objective function with respect to the combination of gas mixing ratios and the injection parameters is calculated according to the following formula to determine how to update the carbon dioxide mixing ratio and the nitrogen mixing ratio, taking the carbon dioxide mixing ratio update as an example:

[0156]

[0157] in, This is the partial derivative of the objective function with respect to the mixing ratio of carbon dioxide; Let be the partial derivative of the objective function with respect to the injection rate.

[0158] Based on the calculated carbon dioxide gradient, update according to the following formula. And the corresponding injection parameters, to gradually approximate the optimal solution of the objective function:

[0159]

[0160] Where α is the learning rate, used to control the step size of each iteration; Q represents the mixing ratio of carbon dioxide in the t-th iteration; (t) Let be the injection rate in the t-th iteration.

[0161] After the carbon dioxide mixing ratio is updated, the nitrogen mixing ratio will be...

[0162] Finally, all simulation results are compared, and the target mixing ratio combination (i.e., the combination including the target mixing ratio and the corresponding injection parameters) with the maximum first total recovery rate (i.e., the first total recovery rate prediction data is greater than the first preset threshold) is selected:

[0163] BestMix = argmax(R total_1 )

[0164] BestMix is ​​the combination of the target mixing ratio and the corresponding injection parameters.

[0165] It should be noted that the above R total_1 Applied to the theoretical model level, it focuses on rapid iteration and convergence. By selecting theoretically feasible target gas mixing ratios, it provides a data foundation for further screening of practically feasible first target gas mixing ratios.

[0166] In some embodiments, inputting the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir in S102 above may, in specific implementation, include:

[0167] The target gas mixing ratio combination is input into the target three-dimensional geological model of the oil and gas reservoir to determine the second total recovery rate corresponding to the target gas mixing ratio combination and output the second simulation result, which includes the second total recovery rate prediction data.

[0168] Accordingly, selecting a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations based on the output second simulation result includes:

[0169] By comparing the second total recovery rate prediction data corresponding to the target gas mixing ratio combination, a first target gas mixing ratio combination in which the second total recovery rate prediction data is greater than a second preset threshold is selected from the target gas mixing ratio combinations as the actually feasible first target gas mixing ratio combination, wherein the second preset threshold is greater than the first preset threshold.

[0170] Specifically, the aforementioned target gas mixing ratio combination can include a theoretically feasible or theoretically optimal combination of target mixing ratios and corresponding injection parameters, such as a combination of target mixing ratios for carbon dioxide and nitrogen, and corresponding injection parameters. Based on the theoretically optimal target gas mixing ratio combination, a practically feasible or actually optimal first target gas mixing ratio combination can be selected to provide a basis for the actual injection process.

[0171] The target gas mixing ratio combination can be input into the target three-dimensional geological model of the oil and gas reservoir. Simulation analysis is then performed to calculate the secondary total recovery rate (GRP) for each target gas mixing ratio combination and the corresponding injection parameters (the secondary GRP can be understood as the actual total recovery rate of the reservoir area), generating and outputting GRP prediction data. The GRP prediction data can be compared to select a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations; that is, selecting the practically optimal first target gas mixing ratio combination and its corresponding injection parameters. If the GRP prediction data corresponding to the first target gas mixing ratio combination (or the GRP prediction data under the first target gas mixing ratio combination) is greater than a second preset threshold, then the GRP prediction data corresponding to the first target gas mixing ratio combination is practically optimal. The second preset threshold can be greater than the first preset threshold, meaning the selected first target gas mixing ratio combination is better than the selected target gas mixing ratio combination. The second preset threshold can be set according to actual needs; this specification does not specifically limit it.

[0172] In some embodiments, the determination of the second total recovery rate corresponding to the target gas mixing ratio combination described above may, in specific implementation, include:

[0173] The second total recovery rate is determined using the following formula:

[0174]

[0175] Among them, R total_2 φ(x,y,z) represents the second overall recovery rate; φ(x,y,z) represents the porosity distribution function; S(x,y,z) represents the crude oil saturation distribution function. This refers to the multi-physics coupling effect in the gas-fuel displacement process. This refers to the mixing ratio of carbon dioxide; κ represents the nitrogen mixing ratio; Q represents the injection flow rate in the injection parameters; P represents the formation pressure; T represents the formation temperature; and κ represents the reservoir permeability.

[0176] Specifically, the above for:

[0177]

[0178] Among them, g phase This is a phase model representing the solubility and phase transition characteristics of a carbon dioxide-nitrogen mixture under different formation pressures and temperatures; h flow This is a seepage model, representing the seepage characteristics; m injection The injection model represents the impact of different gas mixing ratios and corresponding injection rates on the secondary total recovery rate.

[0179] The above phase model g phase It can be represented as:

[0180]

[0181] in, It is the compressibility factor for carbon dioxide; Z is the compressibility factor for nitrogen. mix The total compressibility factor of the gas mixture.

[0182] The above seepage model h flow It can be represented as:

[0183]

[0184] Where μ is the fluid viscosity; ▽P is the pressure gradient; ρ is the fluid density; Q is the injection rate; and d is the diameter of the seepage channel.

[0185] The above injection model m injection It can be represented as:

[0186]

[0187] Where α1, β, and γ are empirical coefficients related to reservoir characteristics.

[0188] In some embodiments, in order to quickly select a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations, an optimization objective function for the second total recovery rate can be set before running the simulation analysis:

[0189]

[0190] Then, the objective function is maximized:

[0191]

[0192] When running the simulation analysis, by adjusting R... total_2 By calculating the partial derivatives, the gradient information is obtained:

[0193]

[0194] The carbon dioxide mixing ratio, nitrogen mixing ratio, and injection rate are updated incrementally using a gradient descent method:

[0195]

[0196] The iteration can stop when the gradient change is less than the preset gradient threshold, thus obtaining the actual optimal gas mixing ratio and injection rate, which is the first target gas mixing ratio combination mentioned above.

[0197] It should be noted that the above R total_2 When applied to practical applications, it reflects the "spatial heterogeneity" of the recovery rate and can provide a basis for adjusting the specific gas mixing ratio and injection parameters in field schemes.

[0198] In some embodiments, when selecting a practically feasible first target gas mixing ratio combination, it may also be considered to calculate the first sensitivity of the second total recovery rate to changes in the target mixing ratio of carbon dioxide and the second sensitivity of the second total recovery rate to changes in the target mixing ratio of nitrogen, then compare the first sensitivity, select the first target mixing ratio of carbon dioxide with a first sensitivity less than a first preset sensitivity threshold, compare the second sensitivity, select the second target mixing ratio of nitrogen with a second sensitivity less than a second preset sensitivity threshold, and use the first target mixing ratio of carbon dioxide and the second target mixing ratio of nitrogen as a practically feasible first target gas mixing ratio combination.

[0199] Sensitivity quantifies the impact of ratio fluctuations on harvesting performance. Lower sensitivity indicates less sensitivity to ratio changes, suggesting a more stable ratio combination suitable for practical application. The first and second preset sensitivity thresholds can be set according to actual needs; this specification does not impose specific limitations on them.

[0200] The first sensitivity of the second overall recovery rate to changes in the target mixing ratio of carbon dioxide can be calculated using the following formula:

[0201]

[0202] The second sensitivity of the second total recovery rate to changes in the target mixing ratio of nitrogen can be calculated using the following formula:

[0203]

[0204] In some embodiments, when selecting a practically feasible first target gas mixing ratio combination, in addition to considering the second total recovery rate, operating costs and technical feasibility can also be considered to construct a weighted multi-objective optimization model:

[0205] Optimal solution = argmax(w1·R) total_2 +w2·C+w3·F)

[0206] Among them, R total_2 C represents the second overall recovery rate; F represents the cost; w1, w2, and w3 are the weighting coefficients for the second overall recovery rate, cost, and feasibility, respectively; argmax refers to the input parameters that yield this maximum value. By adjusting the weighting coefficients, a balance can be struck between different objectives.

[0207] By solving a multi-objective optimization model, the optimal combination of the first objective gas mixing ratios is found, which maximizes the multi-objective goals. At this point, the combined scores of the second objective gas mixing ratio combination—total recovery rate, cost, and feasibility—achieve optimality. This provides a more accurate and reliable basis for the actual injection process.

[0208] In some embodiments, selecting the gas mixing ratio combination based on the first target gas mixing ratio combination in S103 above may, in specific implementation, include:

[0209] The first target gas mixing ratio combination is used as the target value, and the current gas mixing ratio combination is adjusted once until the first error value between the first target gas mixing ratio combination and the adjusted gas mixing ratio combination is less than the first preset error threshold.

[0210] The adjusted gas mixing ratio combination is used as the selected gas mixing ratio combination.

[0211] Specifically, the aforementioned current gas mixing ratio combination can be the combination of current gas mixing ratios monitored in real time on-site, along with the corresponding injection parameters. This current gas mixing ratio combination can include the current mixing ratio of carbon dioxide and the current mixing ratio of nitrogen. Based on the first target gas mixing ratio combination, the current gas mixing ratio combination can be adjusted to improve the injection effect during actual injection, ensuring a significant increase in oil and gas recovery.

[0212] The current mixing ratio of carbon dioxide can be determined according to the following formula:

[0213]

[0214] The current mixing ratio of nitrogen can be determined according to the following formula:

[0215]

[0216] in, This represents the current mixing ratio of carbon dioxide; This represents the current mixing ratio of nitrogen. The flow rate of carbon dioxide; This represents the flow rate of nitrogen gas.

[0217] The above-mentioned adjustment of the current gas mixing ratio, using the first target gas mixing ratio as the target value, may include:

[0218] The combination of the first target gas mixing ratio is taken as the target value Φ. target The gas flow rate is adjusted through a real-time control algorithm to ensure that the first target gas mixing ratio combination matches the adjusted gas mixing ratio combination Φ. current The first error value is less than the first preset error threshold (the first error is minimized). The first preset error threshold can be set according to actual needs, and this specification does not specify it.

[0219] The formula for the real-time control algorithm is as follows:

[0220] (This formula is used to adjust or control the current mixing ratio of carbon dioxide) or

[0221] (This formula is used to adjust or control the current mixing ratio of nitrogen.)

[0222] Among them, K p K i K dHere, e(τ) represents the gain coefficients of the proportional, integral, and derivative controllers, respectively; e(τ) is the first error value between the first target gas mixing ratio combination and the gas mixing ratio combination after one adjustment at any time τ; e(t) is the first error value between the first target gas mixing ratio combination and the gas mixing ratio combination after one adjustment at the current time t, which can be determined according to the following formula:

[0223] e(t) = Φ target -Φ current

[0224] Based on the real-time monitoring of the current gas mixing ratio, the flow rates of carbon dioxide and nitrogen can be dynamically adjusted through a feedback control system to achieve closed-loop control.

[0225] After obtaining an adjusted gas mixing ratio combination, it can be used as the selected gas mixing ratio combination. Based on the selected gas mixing ratio combination, it can be uniformly mixed by a mixing device to form the target gas mixture, preparing for the injection process.

[0226] In some embodiments, before injecting into an underground oil and gas reservoir, the optimal injection point (i.e., the target location mentioned above) can be determined first, and then the gas mixture can be injected into the optimal injection point of the oil and gas reservoir to ensure maximum recovery and maximum coverage. The optimal injection point can be determined by setting and solving an optimization objective. The optimization objective can be:

[0227]

[0228] Where V represents the three-dimensional space of the oil and gas reservoir; (x,y,z) represents the location coordinates; ψ(x,y,z) is the coverage function of the injected gas, used to describe the distribution of gas in the reservoir; and R(x,y,z) represents the recovery rate at each location.

[0229] In some embodiments, the oil and gas reservoir monitoring data obtained at the target location in S104 above is compared with the second simulation results, and the gas mixing ratio is adjusted according to the comparison results. In specific implementation, this may include:

[0230] Calculate the second error value between the oil and gas reservoir monitoring data and the second simulation results;

[0231] Based on the second error value, determine the adjustment amount for the secondary adjustment of the gas mixing ratio combination;

[0232] Based on the adjustment amount and oil and gas reservoir monitoring data, the gas mixing ratio combination is adjusted a second time to obtain the gas mixing ratio combination after the second adjustment.

[0233] Specifically, after injecting the target gas mixture into the target location of the underground oil and gas reservoir, the reservoir can be monitored in real time, and reservoir monitoring data (such as pressure, temperature, fluid composition, gas injection volume, and flow rate) can be acquired. This reservoir monitoring data can be compared with the results of the second simulation described above. Based on the comparison results, the gas mixing ratio can be adjusted (secondarily adjusted) so that the adjusted (secondarily adjusted) gas mixing ratio achieves optimal injection results during actual injection, while significantly improving recovery rate and reducing overall injection costs.

[0234] The second error value calculated above between the reservoir monitoring data and the second simulation results may include:

[0235] Calculate the second error value using the following formula:

[0236] E(t)=X(t)-X sim (t)

[0237] Where E(t) is the second error value between the oil and gas reservoir monitoring data at the current time t and the second simulation result; X(t) is the actual monitoring value; X sim (t) Simulated prediction (e.g., second total recovery rate prediction).

[0238] The adjustment amount for secondary adjustment of the gas mixing ratio combination based on the second error value may include:

[0239] The adjustment amount for secondary adjustments to the gas mixing ratio combination is determined using the following formula:

[0240]

[0241] Where Δu(t) is the adjustment amount; K p K i K d These are the gain coefficients of the proportional, integral, and derivative controllers, respectively; E(τ) is the second error value between the oil and gas reservoir monitoring data at any time τ and the second simulation result; E(t) is the second error value between the oil and gas reservoir monitoring data at the current time t and the second simulation result.

[0242] The above-mentioned secondary adjustment of the gas mixing ratio based on the adjustment amount and oil and gas reservoir monitoring data may include:

[0243] The gas mixing ratio combination is adjusted a second time according to the following formula:

[0244] u(t)=u initial +Δu(t)

[0245] Where u(t) can represent the gas mixing ratio combination after secondary adjustment; u initialThis represents oil and gas reservoir monitoring data; Δu(t) represents the adjustment amount.

[0246] By making secondary adjustments to the gas mixing ratio, the recovery rate can be further optimized.

[0247] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0248] Enhanced oil recovery: By optimizing the mixing of carbon dioxide and nitrogen and combining it with geological modeling and simulation analysis, this invention can find the optimal gas mixing ratio and injection parameters under different conditions, thereby significantly improving the oil and gas recovery rate.

[0249] Cost reduction: Compared to using high-cost carbon dioxide injection technology alone, this invention reduces the overall injection cost by rationally combining nitrogen and carbon dioxide, thereby optimizing the economics of improving the recovery rate.

[0250] Optimized injection effect: This invention uses a target three-dimensional geological model of the oil and gas reservoir for detailed simulation, which can more accurately predict and optimize the impact of different gas mixing ratios on the recovery rate, thereby improving the efficiency and effectiveness of the injection process.

[0251] Enhanced adaptability: By monitoring and adjusting the injection rate and mixing ratio of the gas mixture in real time, this invention can dynamically optimize the gas mixture according to the actual conditions of the oil and gas reservoir, thereby better adapting to the characteristics and needs of different oil and gas reservoirs.

[0252] Risk reduction: By comprehensively applying geological models and simulation analysis, potential problems can be predicted before actual injection, reducing the risks in actual operation and improving the overall safety and stability of the operation.

[0253] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. For details, please refer to the foregoing descriptions of the relevant processing embodiments; they will not be repeated here.

[0254] The foregoing description of this method is for illustrative purposes only and describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0255] In a specific implementation scenario, refer to Figure 2 As shown, the following steps may be included:

[0256] Step S1: Collect carbon dioxide and nitrogen to meet the needs of subsequent mixing and injection.

[0257] Step S2: Establish a three-dimensional geological model of the oil and gas reservoir. The model includes the porosity, permeability, fluid properties, etc. of the oil and gas reservoir, so as to accurately predict the changes in recovery rate under different injection conditions.

[0258] Step S3: Set the mixing ratio. In the simulation model, set various mixing ratios and injection parameters for carbon dioxide and nitrogen gases. The purpose is to optimize the mixing ratio and injection parameters by simulating and analyzing the impact of different conditions on the recovery rate.

[0259] Step S4: Run simulation analysis to evaluate the impact of different mixing ratios and injection parameters on the recovery rate, and determine the theoretically optimal mixing ratios and injection parameters to improve the actual injection effect.

[0260] Step S5: Select the optimal solution. Based on the simulation results, select the optimal mixing ratio of carbon dioxide gas and nitrogen gas to provide a basis for the actual injection process.

[0261] Step S6, gas mixing: Carbon dioxide gas and nitrogen gas are mixed in a selected ratio using a mixing device to form a target gas mixture, preparing for the injection process.

[0262] Step S7, gas injection displacement, involves injecting a gas mixture into the underground oil and gas reservoir. The injection hole is set at an optimal location within the oil and gas reservoir to effectively improve oil and gas recovery.

[0263] Step S8, monitoring and optimization: real-time monitoring of pressure, temperature and fluid composition data in the oil and gas reservoir, comparison of actual data with simulation results, and adjustment of the injection rate and mixing ratio of the gas mixture to further optimize the recovery rate.

[0264] Application examples

[0265] Based on the above methods, gas injection to enhance production was carried out on well B3-1 in oilfield A work area, as detailed below:

[0266] 1. The reservoir of well B3-1 in oilfield A area described in this embodiment has the following characteristics: Reservoir type: sandstone reservoir, porosity 18%, permeability 120 mD. Reservoir conditions: formation temperature 80℃, formation pressure 20 MPa, belonging to medium-high pressure reservoir. Residual oil characteristics: recovery rate reaches 50%, residual oil saturation 35%, a typical low-efficiency residual oil distribution area. Current challenges: After adopting traditional water drive technology, the recovery rate of well B3-1 has limited effect, remaining at 28% for a long time, making further improvement difficult. To solve this problem, an optimized method for carbon dioxide and nitrogen mixed injection was adopted according to this invention. Experiments and optimizations were conducted on well B3-1 to explore the optimal process scheme for mixed injection of carbon dioxide (CO2) and nitrogen (N2).

[0267] 2. Carbon dioxide and nitrogen gases are supplied through dedicated high-pressure carbon dioxide and nitrogen storage tanks, with a purity of no less than 99.5%. High-pressure pumps are used to pressurize the carbon dioxide and nitrogen gases to a pressure higher than 25 MPa to ensure that the reservoir injection requirements are met.

[0268] 3. Geological parameters of well B3-1, including porosity, permeability, fluid properties (crude oil viscosity and density), formation pressure, and formation temperature, were collected through well logging, seismic interpretation, and core experiments. The reservoir area was divided into grids using a 50×50×100 grid with a grid resolution of 1m. 3 The inverse distance weighted interpolation (IDW) method was used to interpolate and calculate the porosity and permeability distributions. The relationship between permeability and porosity is: k = k0 · Φ A Where k is the permeability; k0 is the initial permeability; Φ is the porosity; and A is an empirical coefficient. The model was calibrated using historical production and pressure data, and the prediction accuracy of the model was evaluated using the root mean square error (RMSE), with the RMSE value controlled within 0.05.

[0269] 4. Set various mixing ratios and injection parameters, run simulations, and determine the optimal solution. Mixing ratio: Carbon dioxide (CO2) ratio ranges from 50% to 90%, nitrogen (N2) ratio ranges from 10% to 50%. Injection rate: ranges from 200 to 500 m³ / h. 3 / d, using 50m 3 The step size is adjusted by / d. The optimal combination is selected by simulating the impact of each mixing ratio and injection rate on the recovery rate. Multiple schemes are derived through simulation; see [reference needed]. Figure 3 As shown, the recovery rate is 35% under conditions of 50% CO2 + 50% N2. (See also...) Figure 4As shown, the recovery rate was 42% under the condition of 70% CO2 + 30% N2. Under the condition of 90% CO2 + 10% N2, the recovery rate was 41%. Finally, it was determined that the optimal injection rate was 300m³ for 70% CO2 + 30% N2. 3 / d.

[0270] 5. A turbulent mixer is used to uniformly mix CO2 and N2, and a mass flow meter is used to monitor the gas flow rate. The gas flow rate is adjusted in real time to ensure a mixing ratio of 70:30. The mixed gas is injected into the underground oil and gas reservoir of well B3-1. Two injection pipes are installed in the wellbore of well B3-1 to ensure the injection depth of the mixed gas is controlled at a reservoir depth of 3200m, with injection wells located in high-permeability layers. The injection rate is set at 300m / s. 3 / d. Pressure, temperature, and gas flow in the reservoir are monitored in real time using pressure and temperature sensors. Adjustment strategy: When pressure fluctuations exceed 10%, the mixing ratio of carbon dioxide and nitrogen is adjusted. The actual pressure increased from 20 MPa to 22 MPa, and the monitored flow velocity stabilized at 50 m / s. 3 / h, after adjustment, the proportion of CO2 was reduced from 70% to 65%, which further improved the displacement effect.

[0271] 6. Recovery Rate Change: Before injection, the recovery rate of well B3-1 was 28%. After adopting a mixed injection method of 70% CO2 + 30% N2, the recovery rate increased to 42%, a cumulative increase of 14%. Economic Assessment: Compared with using CO2 alone, nitrogen is less expensive. The 70% CO2 + 30% N2 method reduced the operating cost of a single well by 20%.

[0272] This embodiment utilizes an optimized method for injecting a mixture of carbon dioxide and nitrogen, employing a 70% CO2 + 30% N2 injection technology. Compared to traditional waterflooding technology, this method increases the recovery rate by 14%, achieving the expected technical goals. By replacing some of the carbon dioxide with nitrogen, the injection cost is reduced by 20%, making the operation more economical and efficient.

[0273] Although this specification provides the following examples or appendices Figure 5The method or apparatus structure shown may include more or fewer operational steps or module units, depending on conventional or non-inventive methods. In steps or structures where there is no logically necessary causal relationship, the execution order of these steps or the module structure of the apparatus is not limited to the execution order or module structure shown in the embodiments or drawings of this specification. When the method or module structure is applied in actual devices, servers, or terminal products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or drawings (e.g., in parallel processor or multi-threaded processing environments, or even distributed processing or server cluster implementation environments). Based on the above-described carbon dioxide and nitrogen gas mixing injection optimization method, this specification also proposes an embodiment of a carbon dioxide and nitrogen gas mixing injection optimization apparatus. Figure 5 As shown, the device may specifically include the following modules:

[0274] The first selection module 501 can be used to input various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, and select the theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations based on the output first simulation results.

[0275] The second selection module 502 can be used to input the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir, and select the first feasible target gas mixing ratio combination from the target gas mixing ratio combination according to the output second simulation result.

[0276] The mixing module 503 can be used to select a gas mixing ratio combination to form a target gas mixture based on a first target gas mixing ratio combination, the target gas mixture being injected into a target location in an oil and gas reservoir;

[0277] The optimization module 504 can be used to acquire oil and gas reservoir monitoring data from the target location and compare it with the second simulation results. Based on the comparison results, the gas mixing ratio can be adjusted to optimize the actual injection effect.

[0278] In some embodiments, before the first selection module 501, the module can be further used to divide the oil and gas reservoir area into a preset number of grid cells, and to distribute the collected geological data to each grid cell through interpolation to create an initial three-dimensional geological model of the oil and gas reservoir. The preset number is determined based on the total volume of the oil and gas reservoir and the volume of each grid cell. The fluid properties and fluid flow behavior are modeled, and the fluid property modeling results and fluid flow simulation results are coupled into the initial three-dimensional geological model of the oil and gas reservoir to obtain a three-dimensional geological model of the oil and gas reservoir. The fluid properties include fluid density and fluid viscosity, and the fluid flow behavior includes fluid flow rate. The three-dimensional geological model of the oil and gas reservoir is verified, and when the verification is passed, the target three-dimensional geological model of the oil and gas reservoir is obtained.

[0279] In some embodiments, the first selection module 501 can be specifically used to input various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, determine the first total recovery rate corresponding to various gas mixing ratio combinations and output the first simulation result, the first simulation result including the first total recovery rate prediction data; compare the first total recovery rate prediction data corresponding to various gas mixing ratio combinations, and select the target gas mixing ratio combination from various gas mixing ratio combinations where the first total recovery rate prediction data is greater than a first preset threshold, as the theoretically feasible target gas mixing ratio combination.

[0280] In some embodiments, the first selection module 501 may further be used to determine the pressure drop during the injection of each grid cell according to various gas mixing ratio combinations; determine the fluid flow behavior of each grid cell according to the pressure drop; determine the recovery rate of each grid cell according to the fluid flow behavior; and sum the recovery rates of each grid cell to obtain the first total recovery rate corresponding to various gas mixing ratio combinations.

[0281] In some embodiments, the second selection module 502 can be specifically used to input the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir, determine the second total recovery rate corresponding to the target gas mixing ratio combination and output the second simulation result, the second simulation result including the second total recovery rate prediction data; compare the second total recovery rate prediction data corresponding to the target gas mixing ratio combination, select the first target gas mixing ratio combination from the target gas mixing ratio combination when the second total recovery rate prediction data is greater than the second preset threshold, as the practically feasible first target gas mixing ratio combination, the second preset threshold being greater than the first preset threshold.

[0282] In some embodiments, the second selection module 502 described above can also be used to determine the second total recovery rate according to the following formula:

[0283]

[0284] Among them, R total_2 φ(x,y,z) represents the second overall recovery rate; φ(x,y,z) represents the porosity distribution function; S(x,y,z) represents the crude oil saturation distribution function. This refers to the multi-physics coupling effect in the gas-fuel displacement process. This refers to the mixing ratio of carbon dioxide; κ represents the nitrogen mixing ratio; Q represents the injection flow rate in the injection parameters; P represents the formation pressure; T represents the formation temperature; and κ represents the reservoir permeability.

[0285] In some embodiments, the mixing module 503 may be specifically used to take the first target gas mixing ratio combination as the target value, adjust the current gas mixing ratio combination once, until the first error value between the first target gas mixing ratio combination and the adjusted gas mixing ratio combination is less than the first preset error threshold; and take the adjusted gas mixing ratio combination as the selected gas mixing ratio combination.

[0286] In some embodiments, the optimization module 504 can be specifically used to calculate the second error value between the oil and gas reservoir monitoring data and the second simulation result; determine the adjustment amount for secondary adjustment of the gas mixing ratio combination based on the second error value; and perform secondary adjustment of the gas mixing ratio combination based on the adjustment amount and the oil and gas reservoir monitoring data to obtain the gas mixing ratio combination after secondary adjustment.

[0287] As can be seen from the above, the carbon dioxide and nitrogen mixing injection optimization device provided in the embodiments of this specification can dynamically and accurately adjust the gas mixing ratio, significantly improve oil and gas recovery rate, reduce overall injection cost, and improve actual injection effect.

[0288] This specification also provides an electronic device based on the above-described carbon dioxide and nitrogen mixed injection optimization method, including a processor and a memory for storing processor-executable programs / instructions. Specifically, the processor can execute the following steps according to the program / instructions: inputting various gas mixing ratio combinations into a target three-dimensional geological model of the oil and gas reservoir; selecting a theoretically feasible target gas mixing ratio combination from the various gas mixing ratio combinations based on the output of a first simulation result; inputting the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir; selecting a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations based on the output of a second simulation result; selecting a gas mixing ratio combination to form a target gas mixture based on the first target gas mixing ratio combination, the target gas mixture being injected at the target location of the oil and gas reservoir; acquiring oil and gas reservoir monitoring data from the target location and comparing it with the second simulation result; adjusting the gas mixing ratio combination based on the comparison result to optimize the actual injection effect.

[0289] To execute the above instructions more accurately, please refer to... Figure 6 As shown in the embodiments of this specification, another specific electronic device is also provided, wherein the electronic device includes a network communication port 601, a processor 602 and a memory 603, and the above structures are connected by internal cables so that the various structures can perform specific data interaction.

[0290] Specifically, the processor 602 can be used to input various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir; select a theoretically feasible target gas mixing ratio combination from the various gas mixing ratio combinations based on the output first simulation result; input the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir; select a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations based on the output second simulation result; select a gas mixing ratio combination to form a target gas mixture based on the first target gas mixing ratio combination, the target gas mixture being injected into the target location of the oil and gas reservoir; acquire oil and gas reservoir monitoring data from the target location and compare it with the second simulation result; adjust the gas mixing ratio combination based on the comparison result to optimize the actual injection effect.

[0291] The memory 603 can be used to store the corresponding instruction program.

[0292] In this embodiment, the network communication port 601 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0293] In this embodiment, the processor 602 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0294] In this embodiment, the memory 603 may include multiple layers. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0295] This specification also provides a computer storage medium based on the above-described carbon dioxide and nitrogen mixed injection optimization method. The computer storage medium stores a computer program / instruction that, when executed, performs the following: inputting various gas mixing ratio combinations into a target three-dimensional geological model of the oil and gas reservoir; selecting a theoretically feasible target gas mixing ratio combination from the various gas mixing ratio combinations based on the output of a first simulation result; inputting the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir; selecting a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations based on the output of a second simulation result; selecting a gas mixing ratio combination to form a target gas mixture based on the first target gas mixing ratio combination, which is used for injection at the target location of the oil and gas reservoir; acquiring oil and gas reservoir monitoring data from the target location and comparing it with the second simulation result; adjusting the gas mixing ratio combination based on the comparison result to optimize the actual injection effect.

[0296] In this embodiment, the storage medium includes, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), cache, hard disk drive (HDD), or memory card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured according to standards specified in the communication protocol for network connection communication.

[0297] In this embodiment, the specific functions and effects implemented by the program instructions stored in the computer storage medium can be explained in comparison with other implementation methods, and will not be repeated here.

[0298] While this specification provides the steps of operation for the methods described in the embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or client product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. The terms "first," "second," etc., are used to denote names and do not indicate any particular order.

[0299] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0300] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0301] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments of this specification.

[0302] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. This specification can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0303] Although this specification has been described by way of examples, those skilled in the art will recognize that many variations of this specification are possible without departing from its spirit, and it is intended that the appended claims cover such variations without departing from the spirit of this specification.

Claims

1. An optimized method for injecting a mixture of carbon dioxide and nitrogen, characterized in that, include: Various gas mixing ratio combinations are input into the target three-dimensional geological model of the oil and gas reservoir. Based on the first simulation result output, a theoretically feasible target gas mixing ratio combination is selected from various gas mixing ratio combinations. The target gas mixing ratio combination is input into the target three-dimensional geological model of the oil and gas reservoir. Based on the output of the second simulation results, the first feasible target gas mixing ratio combination is selected from the target gas mixing ratio combinations. Based on the first target gas mixing ratio combination, a gas mixing ratio combination is selected to form a target gas mixture, which is used to be injected into the target location of the oil and gas reservoir; Oil and gas reservoir monitoring data are obtained from the target location and compared with the results of the second simulation. The gas mixing ratio is adjusted according to the comparison results to optimize the actual injection effect.

2. The method according to claim 1, characterized in that, The method further includes: The oil and gas reservoir area is divided into a predetermined number of grid cells, and the collected geological data is distributed to each grid cell through interpolation to create an initial three-dimensional geological model of the oil and gas reservoir. The predetermined number is determined based on the total volume of the oil and gas reservoir and the volume of each grid cell. Fluid properties and fluid flow behavior are modeled, and the modeling results of fluid properties and the simulation results of fluid flow are coupled into the initial three-dimensional geological model of the oil and gas reservoir to obtain the three-dimensional geological model of the oil and gas reservoir. The fluid properties include fluid density and fluid viscosity, and the fluid flow behavior includes fluid flow rate. The three-dimensional geological model of the oil and gas reservoir is validated. When the validation is successful, the target three-dimensional geological model of the oil and gas reservoir is obtained.

3. The method according to claim 1, characterized in that, The process of inputting various gas mixing ratios into the target three-dimensional geological model of the oil and gas reservoir includes: Various gas mixing ratios are input into the target three-dimensional geological model of the oil and gas reservoir to determine the first total recovery rate corresponding to the various gas mixing ratios and output the first simulation result, which includes the first total recovery rate prediction data. Accordingly, selecting a theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations based on the output of the first simulation result includes: By comparing the first total recovery rate prediction data corresponding to various gas mixing ratio combinations, a target gas mixing ratio combination in which the first total recovery rate prediction data is greater than a first preset threshold is selected from various gas mixing ratio combinations as a theoretically feasible target gas mixing ratio combination.

4. The method according to claim 2, characterized in that, The determination of the first total recovery rate corresponding to the various gas mixing ratio combinations includes: The pressure drop during the injection of each grid cell is determined based on various gas mixing ratios. Based on the pressure drop, determine the fluid flow behavior of each grid cell; The recovery rate of each grid cell is determined based on the fluid flow behavior. The recovery rates of each grid cell are summed to obtain the first total recovery rate corresponding to various gas mixing ratio combinations.

5. The method according to claim 1, characterized in that, The process of inputting the target gas mixing ratio into the target three-dimensional geological model of the oil and gas reservoir includes: The target gas mixing ratio combination is input into the target three-dimensional geological model of the oil and gas reservoir to determine the second total recovery rate corresponding to the target gas mixing ratio combination and output the second simulation result, which includes the second total recovery rate prediction data. Accordingly, selecting a practically feasible first target gas mixing ratio combination from the target gas mixing ratio combinations based on the output second simulation result includes: By comparing the second total recovery rate prediction data corresponding to the target gas mixing ratio combination, a first target gas mixing ratio combination in which the second total recovery rate prediction data is greater than a second preset threshold is selected from the target gas mixing ratio combinations as the actually feasible first target gas mixing ratio combination, wherein the second preset threshold is greater than the first preset threshold.

6. The method according to claim 5, characterized in that, The determination of the second total recovery rate corresponding to the target gas mixing ratio combination includes: The second total recovery rate is determined using the following formula: Among them, R total_2 φ(x,y,z) represents the second overall recovery rate; φ(x,y,z) represents the porosity distribution function; S(x,y,z) represents the crude oil saturation distribution function. This refers to the multi-physics coupling effect in the gas-fuel displacement process. This refers to the mixing ratio of carbon dioxide; κ represents the nitrogen mixing ratio; Q represents the injection flow rate in the injection parameters; P represents the formation pressure; T represents the formation temperature; and κ represents the reservoir permeability.

7. The method according to claim 1, characterized in that, The step of selecting a gas mixing ratio combination based on a first target gas mixing ratio combination includes: The first target gas mixing ratio combination is used as the target value, and the current gas mixing ratio combination is adjusted once until the first error value between the first target gas mixing ratio combination and the adjusted gas mixing ratio combination is less than the first preset error threshold. The adjusted gas mixing ratio combination is used as the selected gas mixing ratio combination.

8. The method according to claim 1, characterized in that, The step of comparing the oil and gas reservoir monitoring data obtained from the target location with the second simulation results, and adjusting the gas mixing ratio based on the comparison results, includes: Calculate the second error value between the oil and gas reservoir monitoring data and the second simulation results; Based on the second error value, determine the adjustment amount for the secondary adjustment of the gas mixing ratio combination; Based on the adjustment amount and oil and gas reservoir monitoring data, the gas mixing ratio combination is adjusted a second time to obtain the gas mixing ratio combination after the second adjustment.

9. A carbon dioxide and nitrogen mixed injection optimization device, characterized in that, include: The first selection module is used to input various gas mixing ratio combinations into the target three-dimensional geological model of the oil and gas reservoir, and select the theoretically feasible target gas mixing ratio combination from various gas mixing ratio combinations based on the output first simulation results. The second selection module is used to input the target gas mixing ratio combination into the target three-dimensional geological model of the oil and gas reservoir, and select the first feasible target gas mixing ratio combination from the target gas mixing ratio combination based on the output second simulation results. A mixing module is used to select a gas mixing ratio combination to form a target gas mixture based on a first target gas mixing ratio combination, the target gas mixture being injected at a target location in an oil and gas reservoir. The optimization module is used to acquire oil and gas reservoir monitoring data from the target location and compare it with the second simulation results. Based on the comparison results, the gas mixing ratio is adjusted to optimize the actual injection effect.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 8.

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