Evaluation method for early production capacity characteristics of strong heterogeneous carbonate gas reservoir

Abstract

The application discloses a method for evaluating early production capacity characteristics of a strong non-homogeneous carbonate rock gas reservoir, and comprises the following steps: step 1, obtaining the shut-in pressure and the shut-in temperature of a gas well according to special well testing data, and obtaining reservoir percolation parameters through interpretation; step 2, constructing a typical percolation model according to the reservoir percolation parameters; and step 3, correcting the typical percolation model, and using the corrected typical percolation model to evaluate the early production capacity characteristics of the gas well. The application can more effectively describe the early production capacity characteristics of the strong non-homogeneous carbonate rock gas reservoir, thereby providing a strong basis for the exploitation of the gas well.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas exploration and development technology, and in particular relates to an evaluation method for the early production capacity characteristics of strongly heterogeneous carbonate gas reservoirs. Background Technology

[0002] Field practice shows that due to the complexity and heterogeneity of fractured-vuggy carbonate gas reservoirs, it is difficult for Sinian gas wells to reach a near-steady state during well testing. The flow state varies with each working cycle in productivity testing, and the complexity of the reservoirs is mismatched with productivity evaluation methods. Furthermore, current understanding of early-stage productivity changes in low-permeability, highly heterogeneous gas reservoirs focuses more on single issues, such as the slippage effect, starting pressure gradient, high-velocity non-Darcy effect, and establishing curves showing the relationship between unstable unobstructed flow rate and testing time. A systematic and comprehensive methodology for understanding early-stage productivity changes has not yet been developed. This hinders early-stage evaluation and productivity assessment in gas field development. The results of productivity assessment provide weak support for optimizing production organization in developed well areas and designing development scale in undeveloped well areas, representing a key technical problem for early-stage evaluation, developed, and un-evaluated well areas in the Sinian system.

[0003] Patent document CN112576248A discloses a method for early-stage production capacity evaluation and prediction of bottom-water gas reservoirs. The technical solution involves: establishing a steady-state seepage mathematical model for a wellbore unit in a bottom-water gas reservoir; importing wellbore trajectory data and logging permeability data; extracting wellbore trajectory data and logging data from the production zone; and, based on the overall potential distribution function of the bottom-water gas reservoir, coupling the well flow equation and reservoir flow equation to plot the dynamic characteristic curve of gas well inflow, obtain the gas well's unobstructed flow rate, and evaluate the gas well's production capacity. This patent considers the differential distribution of wellbore trajectory and permeability along the wellbore trajectory, resulting in more accurate calculations; it requires less data, only wellbore trajectory and logging data; and it has strong versatility, capable of calculating the production capacity of vertical wells, horizontal wells, highly deviated wells, and meandering wells. However, this method still has the following technical problems in practical applications:

[0004] 1. Well logging data can only describe reservoir information near the wellbore. If the reservoir is highly heterogeneous, using this information to build a model to evaluate production capacity will not reflect the true gas reservoir situation and will lead to cognitive bias.

[0005] 2. The calculated production capacity is only the production capacity at a certain point in time and cannot describe the relationship between production capacity and changes in seepage on the reservoir plane over time.

[0006] For example, patent document CN107563899A discloses a method and apparatus for predicting the production capacity of an oil and gas well. The method includes: acquiring test information of the oil and gas well; determining the inflow dynamic model of the oil and gas well within the current production capacity prediction period based on the test information; determining the production rate within the current production capacity prediction period and the future average formation pressure within the next production capacity prediction period based on the inflow dynamic model of the oil and gas well within the current production capacity prediction period and the future average formation pressure within the next production capacity prediction period; and determining the inflow dynamic model of the oil and gas well within the next production capacity prediction period based on the inflow dynamic model of the oil and gas well within the current production capacity prediction period and the future average formation pressure within the next production capacity prediction period, and predicting the production capacity of the oil and gas well within the next production capacity prediction period. This method can utilize test information obtained from oil or gas testing to determine the inflow dynamics of the oil and gas well at a future production time, thereby enabling the prediction of the future production capacity of the oil and gas well. However, the gas well test information in this method is obtained through gas testing, and the testing time is generally only a few hours. It can only reflect the reservoir seepage in the reformed area. The data obtained in such a short time can only establish a description of the production capacity in the gas well reformed area. If the reservoir is highly heterogeneous, it will produce huge biases in understanding. Summary of the Invention

[0007] The purpose of this invention is to overcome the aforementioned technical problems in the prior art and to provide an evaluation method for the early production capacity characteristics of strongly heterogeneous carbonate gas reservoirs. This invention can more effectively describe the early production capacity characteristics of strongly heterogeneous carbonate gas reservoirs, thereby providing a strong basis for gas well development.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0009] A method for evaluating the early-stage productivity characteristics of strongly heterogeneous carbonate gas reservoirs, the technical solution of which includes the following steps:

[0010] Step 1: Obtain the shut-in pressure and shut-in temperature of the gas well based on the special well test data, and interpret the reservoir seepage parameters.

[0011] Step 2: Construct a typical seepage model based on reservoir seepage parameters;

[0012] Step 3: Correct the typical seepage model and use the corrected typical seepage model to evaluate the early production capacity characteristics of the gas well.

[0013] In step 2, the average permeability within the venting radius at a certain time point after the gas well is opened is first calculated based on the reservoir seepage parameters. Then, the venting radius is calculated based on the average permeability. On the one hand, the dynamic reserves of the gas well within the venting radius are calculated. On the other hand, the gas well productivity coefficient is calculated based on the venting radius and the average permeability. Finally, a typical seepage model is constructed based on the average permeability, venting radius, dynamic reserves of the gas well, and gas well productivity coefficient.

[0014] In step 2, the average permeability is calculated as follows:

[0015] (1)

[0016] In equation (1), For average penetration rate, 10 -3 μm 2 ; t For time, h.

[0017] In step 2, the calculation method for the vent radius is as follows:

[0018] (2)

[0019] In equation (2), For the vent radius, Porosity is dimensionless. C t The overall compressibility coefficient of the formation is expressed in MPa. -1 ; ρ represents the average viscosity of natural gas, in mPa·s.

[0020] In step 2, the calculation method for the dynamic reserves of gas wells within the venting radius is as follows:

[0021] (3)

[0022] In equation (3), This represents the dynamic reserves of gas wells within the venting radius. To constrain water saturation, it is dimensionless; m is the volume factor of the original gas. 3 / m 3 R represents the final recovery rate.

[0023] In step 2, the calculation method for the gas well productivity coefficient is as follows:

[0024] (4)

[0025] In equation (4), The coefficient for the unstable Darcy seepage term, in MPa 2 / (10 4 m 3 / d); This is the formation condition natural gas deviation factor, which is dimensionless; Let K be the average temperature of natural gas in the formation. The pressure of the gas under standard conditions is 0.1013 MPa; The temperature of the gas under standard conditions is 293.16 K.

[0026] In step 2, the typical seepage model constructed is as follows:

[0027] (5)

[0028] in,

[0029] (6)

[0030] In equations (5)-(6), The coefficient for the unstable non-Darcy seepage term, MPa 2 / (10 4 m 3 / d) 2 ; D The non-Darcy seepage coefficient (m) 3 / d) -1 .

[0031] In step 3, after obtaining the corrected typical seepage model, the early production capacity of the gas well is calculated based on the average permeability, gas leakage radius, gas well dynamic reserves and gas well production capacity coefficient, and the production capacity change curve is plotted. The early production capacity characteristics of the gas well are evaluated based on the production capacity change curve.

[0032] In step 3, the typical seepage model is calibrated based on the stable production capacity and initial production capacity of the gas well.

[0033] The stable production capacity of the gas well is obtained based on the evaluation of the stable well test. The initial production capacity of the gas well is calculated based on the test production and test pressure of the gas well. The test production and test pressure of the gas well are obtained based on the oil test data of the gas well.

[0034] The advantages of using this invention are:

[0035] 1. This invention can construct a calibrated typical seepage model based on conventional data. Using this calibrated model, the early production capacity characteristics of strongly heterogeneous carbonate gas reservoirs can be described more effectively. Specifically, this invention can obtain the production capacity situation that changes over time, and with sufficient data, the accuracy rate can reach over 95%. This overcomes the problems of large deviations and unclear production guidance in earlier methods, and provides a strong basis for gas well development.

[0036] 2. Practice shows that gas well productivity changes over time. However, in actual research and application, gas well productivity is described in a fragmented manner, rather than continuously. This often deviates from the actual geological conditions, and the productivity evaluation results lack a series of isolated data with practical guiding significance. The specific method described in this invention can solve these technical problems. After adopting this invention, the productivity situation that changes over time can be obtained, which solves the problem of unclear production guidance and provides a strong basis for gas well exploitation. Attached Figure Description

[0037] Figure 1 This is a flowchart of the present invention;

[0038] Figure 2 This is a schematic diagram illustrating the calculation of average permeability in step 2.

[0039] Figure 3 The production capacity change curve plotted in step 3;

[0040] Figure 4 This is a graph showing the production capacity change of well MX108. Detailed Implementation

[0041] In the process of production capacity evaluation, it is known from the connotation of gas well production capacity that gas wells with the same absolute unobstructed flow rate may have different potential production capacities. If a gas well has large dynamic reserves but low permeability, its production capacity is often low; conversely, if a gas well has small dynamic reserves but high permeability, it exhibits high production capacity, such as fractured gas wells. Therefore, in addition to the absolute unobstructed flow rate, it is necessary to clarify the variation law of the absolute unobstructed flow rate of a gas well, as well as the key indicators constituting the absolute unobstructed flow rate, such as dynamic reserves, flow capacity, and their relationship with time. These are also important to pay attention to and master. Specifically, production capacity evaluation should include: the time point for production capacity description and the absolute unobstructed flow rate, its trend, the dynamic reserves within the radius already affected by the gas well pressure drop funnel at the current time point, and the current seepage capacity of the seepage system. Based on this, this invention discloses an evaluation method for the early production capacity characteristics of strongly heterogeneous carbonate gas reservoirs. This method can obtain the production capacity situation that changes continuously over time, and can more effectively describe the early production capacity characteristics of strongly heterogeneous carbonate gas reservoirs. Figure 1 As shown, its technical solution includes the following steps:

[0042] Step 1: Obtain the shut-in pressure and shut-in temperature of the gas well based on the specific well test data, and interpret the reservoir seepage parameters. Once the shut-in pressure and shut-in temperature of the gas well are obtained, the reservoir seepage parameters can be interpreted using conventional surgical methods in this field.

[0043] Step 2: Construct a typical seepage model based on the reservoir seepage parameters obtained in Step 1. Specifically, after obtaining the reservoir seepage parameters, first calculate the average permeability within the vent radius at a certain time point after the gas well is opened, based on the reservoir seepage parameters. This time point can be any time point. Then, calculate the vent radius based on the average permeability. Next, calculate the dynamic reserves of the gas well within the vent radius, and calculate the gas well productivity coefficient based on the vent radius and average permeability. Finally, construct a typical seepage model based on the average permeability, vent radius, dynamic reserves of the gas well, and gas well productivity coefficient.

[0044] Furthermore, the calculation methods for average permeability, vent radius, dynamic reserves of gas wells, and gas well productivity coefficient are as follows:

[0045] like Figure 2 As shown, the average permeability is calculated as follows:

[0046] (1)

[0047] In equation (1), For average penetration rate, 10 -3 μm 2 ; t For time, h.

[0048] The method for calculating the vent radius is as follows:

[0049] (2)

[0050] In equation (2), For the vent radius, Porosity is dimensionless. C t The overall compressibility coefficient of the formation is expressed in MPa. -1 ; ρ represents the average viscosity of natural gas, in mPa·s.

[0051] The method for calculating the dynamic reserves of gas wells within the venting radius is as follows:

[0052] (3)

[0053] In equation (3), This represents the dynamic reserves of gas wells within the venting radius. To constrain water saturation, it is dimensionless; m is the volume factor of the original gas. 3 / m 3 R represents the final recovery rate.

[0054] The calculation method for the gas well productivity coefficient is as follows:

[0055] (4)

[0056] In equation (4), The coefficient for the unstable Darcy seepage term, in MPa 2 / (10 4 m 3 / d); This is the formation condition natural gas deviation factor, which is dimensionless; Let K be the average temperature of natural gas in the formation. The pressure of the gas under standard conditions is 0.1013 MPa; The temperature of the gas under standard conditions is 293.16 K.

[0057] After obtaining the average permeability, vent radius, dynamic reserves of the gas well, and gas well productivity coefficient, a typical seepage model is constructed based on the average permeability, vent radius, dynamic reserves of the gas well, and gas well productivity coefficient:

[0058] (5)

[0059] in,

[0060] (6)

[0061] In equations (5)-(6), The coefficient for the unstable non-Darcy seepage term, MPa 2 / (10 4 m 3 / d) 2 ; D The non-Darcy seepage coefficient (m) 3 / d) -1 .

[0062] In step 3, the typical seepage model is corrected based on the stable production capacity and initial production capacity of the gas well. The stable production capacity can be obtained from the stable well test evaluation, while the initial production capacity can be calculated based on the tested production and pressure of the gas well, which can be obtained from the well's oil testing data. After obtaining the corrected typical seepage model, the early production capacity of the gas well is calculated based on the average permeability, vent radius, dynamic reserves, and production capacity coefficient, and a production capacity change curve is plotted. The plotted production capacity change curve is shown in the figure below. Figure 3 As shown, the early production capacity characteristics of a gas well can finally be evaluated based on the production capacity change curve.

[0063] The method described in this invention, after being developed and designed by the applicant and verified through years of experiments and numerous practical data, can now be effectively applied to the evaluation of early-stage production characteristics in highly heterogeneous carbonate gas reservoirs. The following practical verification method is provided to validate this invention:

[0064] Verification conditions: Well MX108 in the Dengsiqiang heterogeneous carbonate gas reservoir in the Sichuan Basin.

[0065] Verification process:

[0066] Step 1: Obtain the shut-in pressure and shut-in temperature of the gas well based on the specialized well test data, and interpret the reservoir permeability parameters. Specifically, a specialized well test was conducted on well MX108 (pressure gauge number 204409), at a depth of 5034.125m. 278-hour shut-in pressure recovery data was obtained, showing a pressure recovery from 52.35 MPa to 59.45 MPa. The shut-in temperature was measured at 152.6℃. The pressure recovery data was interpreted to yield permeability of 1.26 × 10⁻⁶ for both the near and far well areas. -3 μm 2 and 4.64×10 -3 μm 2 .

[0067] Step 2: Construct a typical seepage model based on reservoir seepage parameters, and calculate the average permeability, radius of influence, etc. , Values ​​changing over time

[0068] Step 3: The production capacity of the model constructed using this invention at the oil testing time point is 60 × 10⁻⁶. 4 m 3 / d, while the oil testing data calculates the initial production capacity of the well to be 62×10 4 m 3 / d.

[0069] Verification results: such as Figure 4 As shown, compared with oil well test data, the present invention has higher accuracy and an accuracy rate of over 95%. Therefore, the present invention can accurately evaluate and continuously describe the early production capacity characteristics of gas wells.

[0070] The above description is merely a specific embodiment of the present invention. Any feature disclosed in this specification may be replaced by other equivalent or similar features unless otherwise specified. All features or steps in the disclosed methods or processes may be combined in any way, except for mutually exclusive features and / or steps.

Claims

1. An evaluation method for the early-stage productivity characteristics of strongly heterogeneous carbonate gas reservoirs, characterized in that... Includes the following steps: Step 1: Obtain the shut-in pressure and shut-in temperature of the gas well based on the special well test data, and interpret the reservoir seepage parameters. Step 2: Construct a typical seepage model based on reservoir seepage parameters; Step 3: Correct the typical seepage model and use the corrected typical seepage model to evaluate the early production capacity characteristics of the gas well. In step 2, the average permeability within the venting radius at a certain time point after the gas well is opened is first calculated based on the reservoir seepage parameters. Then, the venting radius is calculated based on the average permeability. On the one hand, the dynamic reserves of the gas well within the venting radius are calculated. On the other hand, the gas well productivity coefficient is calculated based on the venting radius and the average permeability. Finally, a typical seepage model is constructed based on the average permeability, venting radius, dynamic reserves of the gas well, and gas well productivity coefficient. In step 2, the average permeability is calculated as follows: （1） In equation (1), For average penetration rate, 10 -3 μm 2 ; t For time, h; In step 2, the calculation method for the vent radius is as follows: （2） In equation (2), For the vent radius, Porosity is dimensionless; C t The overall compressibility coefficient of the formation is given in MPa. -1 ; The average viscosity of natural gas is given in mPa·s. In step 2, the calculation method for the dynamic reserves of gas wells within the venting radius is as follows: （3） In equation (3), This represents the dynamic reserves of gas wells within the venting radius. To constrain water saturation, it is dimensionless; m is the volume factor of the original gas. 3 / m 3 R represents the final recovery rate, and h represents the reservoir thickness. In step 2, the calculation method for the gas well productivity coefficient is as follows: （4） In equation (4), The coefficient for the unstable Darcy seepage term, in MPa 2 / (10 4 m 3 / d); This is the formation condition natural gas deviation factor, which is dimensionless; Let K be the average temperature of natural gas in the formation. The pressure of the gas under standard conditions is 0.1013 MPa; The temperature under standard gas conditions is 293.16 K; h is the reservoir thickness. In step 2, the typical seepage model constructed is as follows: （5） in, （6） In equations (5)-(6), The coefficient for the unstable non-Darcy seepage term, MPa 2 / (10 4 m 3 / d) 2 ; D The non-Darcy seepage coefficient (m) 3 / d) -1 h is the reservoir thickness, and p is the formation pressure.

2. The evaluation method for early-stage productivity characteristics of strongly heterogeneous carbonate gas reservoirs according to claim 1, characterized in that: In step 3, after obtaining the corrected typical seepage model, the early production capacity of the gas well is calculated based on the average permeability, gas leakage radius, gas well dynamic reserves and gas well production capacity coefficient, and the production capacity change curve is plotted. The early production capacity characteristics of the gas well are evaluated based on the production capacity change curve.

3. The evaluation method for early-stage productivity characteristics of strongly heterogeneous carbonate gas reservoirs according to claim 1, characterized in that: In step 3, the typical seepage model is calibrated based on the stable production capacity and initial production capacity of the gas well.

4. The evaluation method for early-stage productivity characteristics of strongly heterogeneous carbonate gas reservoirs according to claim 3, characterized in that: The stable production capacity of the gas well is determined based on the evaluation of stable well testing conducted on the gas well.

5. The evaluation method for early-stage productivity characteristics of strongly heterogeneous carbonate gas reservoirs according to claim 4, characterized in that: The initial production capacity of the gas well is calculated based on the test production and test pressure of the gas well.

6. The evaluation method for early-stage productivity characteristics of strongly heterogeneous carbonate gas reservoirs according to claim 5, characterized in that: The test production and test pressure of a gas well are derived from the well's oil testing data.

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