Gas storage geologic body injection-production operation early warning method

Abstract

A gas storage geologic body injection-production operation early warning method belongs to the technical field of underground gas storage injection-production operation safety monitoring, and comprises the following steps: 1, establishing a microseism event database; 2, calculating the magnitude risk coefficient of each micro-seismic event; 3, establishing a high-precision three-dimensional model of the geologic body of the underground gas storage; 4, projecting the microseism event into the three-dimensional model, and carrying out correlation analysis; 5, calculating a weak point risk coefficient of each microseismic event; 6, calculating a frequency risk coefficient under the same gas injection and production condition; and 7, comprehensively judging the risk coefficient of the geologic body. The method is easy and feasible to use, the risk coefficient of the microseism event can be rapidly and accurately obtained, and a certain reference effect is achieved for geological evaluation, injection-production operation and the like of an underground gas storage.

Description

Technical Field

[0001] The invention belongs to the technical field of safety monitoring of injection and production operation of underground gas storage reservoirs, and in particular relates to an early warning method for injection and production operation of a geological body of a gas storage reservoir. Background Art

[0002] According to statistics, underground leakage accidents account for 43.8% of the safety accidents in underground gas storage operations in the world. The geological conditions of sandstone gas reservoirs in eastern my country are complex, and faults are well developed. The safety of injection and production operations of underground gas storage geological bodies is the focus of attention during the injection and production operations of gas storages.

[0003] At present, the early warning of injection and production operation of gas storage geological bodies in China mainly uses the previous evaluation data and single-point monitoring data, such as temperature, pressure, saturation test, injection and production gas profile, well test and other data, to conduct comprehensive analysis, draw a comprehensive curve of storage capacity and apparent formation pressure, and comprehensively evaluate the injection and production risks of geological bodies. This method has a long cycle and low monitoring accuracy. It often takes a complete injection and production cycle to judge the injection and production operation status of the geological body, and it is impossible to achieve real-time early warning. Therefore, it is necessary to monitor based on real-time data and establish a systematic, reliable, and real-time early warning method.

[0004] The prior art CN113253344B discloses a method for realizing underground gas storage pressure increase warning based on microseismic monitoring technology. This patent only uses frequency anomaly index and magnitude anomaly index for simple prediction, without considering the spatial coordinates and time of each microseismic event and the relationship between the weak points of the geological body and the injection and production operation status. The evaluation method is relatively one-sided. Therefore, it is necessary to comprehensively judge the geological body risk coefficient under the current injection and production operation conditions based on the evaluation of the spatial relationship between microseismic events and the weak points of the geological body, and the time relationship with the injection and production gas volume, formation pressure and other operating parameters, so that the evaluation method is accurate and the early warning method is more effective. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes: a method for early warning of injection and production operation of a gas storage geological body, comprising the following steps:

[0006] Step 1: Establish a microseismic event database;

[0007] Step 2: Calculate the magnitude risk coefficient of each microseismic event;

[0008] Step 3: Establish a high-precision three-dimensional model of the underground gas storage geological body;

[0009] Step 4: Project the microseismic events into the 3D model and conduct correlation analysis;

[0010] Step 5: Calculate the weak point risk factor of each microseismic event;

[0011] Step 6: Calculate the frequency risk coefficient under the same gas injection and production conditions;

[0012] Step 7: Comprehensively determine the risk factor of the geological body.

[0013] Furthermore, the step 1: using the microseismic monitoring system to record the time T of the microseismic event in real time i , spatial position coordinates (X i , Y i , Z i ), magnitude M i , analyze the source mechanism and establish a microseismic event database.

[0014] Furthermore, the step 2: read the total number of samples N in the database and the magnitude M of each microseismic event i , calculate the magnitude risk coefficient α of each microseismic event.

[0015] Furthermore, the calculation method is as follows: first calculate the arithmetic mean of the magnitudes of all microseismic events that have occurred, then calculate the ratio of the magnitude of the current microseismic event to the arithmetic mean of the magnitudes of historical microseismic events, and finally take the natural logarithm to calculate the magnitude risk coefficient α, the formula is as follows:

[0016]

[0017] Where e is a natural constant. When the magnitude of the microseismic event detected this time is greater than or equal to 0, that is, M i When ≥0, it is high risk, and its risk coefficient α is specified i =100; when α i ≤e is low risk, and when 10≥α i >e is medium risk, when α i ≥10 indicates high risk.

[0018] Furthermore, the step three is to establish a high-precision three-dimensional model of the underground gas storage geological body, describe the factors affecting the sealing of the geological body, such as the overburden, blocking faults, closure overflow points, natural gas reservoirs, and underlying supporting layers, as well as the spatial position of each wellbore, cementing quality, and casing quality.

[0019] Furthermore, the fourth step is to project the microseismic events onto the three-dimensional model, conduct correlation analysis between the microseismic frequent locations and the main fault / caprock weak zone / wellbore location; calculate the spatial position coordinates (X i , Y i , Z i ) and each fault plane, caprock weak zone, bottom support weak zone, oil and gas boundary, and wellbore, and the minimum value is L i .

[0020] Furthermore, the step 5: Calculate the risk factor β of the weak point of each microseismic event i ,

[0021] β i =L i / R

[0022] The positioning error of the microseismic monitoring system is R;

[0023] When the distance between the earthquake source and the weak point is less than 5 times the spatial positioning accuracy, that is, β i ≤5 is high risk; when the distance between the earthquake source and the weak point is greater than 5 times and less than 10 times the spatial positioning accuracy, that is, 10≥β i When β>5, it is medium risk; when the distance between the earthquake source and the weak point is greater than 10 times the spatial positioning accuracy, and β i When >10, it is low risk.

[0024] Furthermore, the step six: calculating the relationship between microseismic events and gas injection and production volume and formation pressure, and determining the frequency risk coefficient γ under the same gas injection and production conditions i .

[0025] Further, first, determine the statistical unit;

[0026] Then the number of microseismic events NS in each statistical unit in the database is counted.

[0027] Finally, calculate the frequency risk coefficient γ i , determine the risk to the geological body under each gas injection and production volume or formation pressure condition:

[0028]

[0029] Where e is a natural constant, when γ i ≤e is low risk, and when 10≥α i >e is medium risk, when α i ≥10 indicates high risk.

[0030] Furthermore, the step 7: comprehensively judge the geological body risk coefficient δ i :

[0031]

[0032] When δ i When it is greater than 50, it is a high risk, and the injection and production volume should be reduced; when δ i When it is less than 50, it is medium-low risk.

[0033] The beneficial effects of the present invention are as follows: based on real-time monitoring data, the present invention establishes a set of real-time early warning methods for geological body injection and production operation safety, realizes real-time regulation of injection and production gas volume, and prevents safety accidents such as formation sanding and geological body leakage. The invention is simple and feasible to use, and can quickly obtain relatively accurate risk coefficients for microseismic events, which plays a certain reference role in geological evaluation, injection and production operation, etc. of underground gas storage. DETAILED DESCRIPTION

[0034] Example 1

[0035] In order to make the technical means and objectives of the present invention easy to understand, the present invention is further described below in combination with specific implementation methods. A method for early warning of injection and production operation of a geological body of a gas storage reservoir comprises the following steps:

[0036] Step 1: Establish a microseismic event database;

[0037] Step 2: Calculate the magnitude risk coefficient of each microseismic event;

[0038] Step 3: Establish a high-precision three-dimensional model of the underground gas storage geological body;

[0039] Step 4: Project the microseismic events into the 3D model and conduct correlation analysis between the microseismic frequent locations and the main fault / caprock weak zone / wellbore location;

[0040] Step 5: Calculate the weak point risk factor of each microseismic event;

[0041] Step 6: Calculate the frequency risk coefficient under the same gas injection and production conditions;

[0042] Step 7: Comprehensively determine the risk factor of the geological body.

[0043] The present invention provides a method for early warning of geological body injection and production risks in an underground gas storage reservoir. The method utilizes microseismic monitoring technology and distributed fiber optic acoustic sensing technology (hereinafter referred to as DAS) to monitor in real time the response characteristics of the geological body during the injection and production operation, analyzes the temporal and spatial distribution laws and attribute characteristics of microseismic events, establishes a relationship model between injection and production operation data, geological body risk assessment information and microseismic events, quantitatively evaluates the geological body risk coefficient under the current injection and production plan, predicts microseismic events that may be induced in the future and their impact on the safe operation of the geological body, and realizes real-time monitoring and early warning.

[0044] The specific technical solutions are as follows:

[0045] Step 1: Use the microseismic monitoring system to record the time T of microseismic events in real time i , spatial position coordinates (X i , Y i , Z i ), magnitude Mi , analyze the focal mechanism (strike, dip, slip angle) generated, and establish a microseismic event database.

[0046] Step 2: Read the total number of samples N in the database and the magnitude M of each microseismic event i , calculate the magnitude risk coefficient α of each microseismic event. The calculation method is: first calculate the arithmetic mean of the magnitudes of all microseismic events that have occurred, then calculate the ratio of the magnitude of the current microseismic event to the arithmetic mean of the magnitudes of historical microseismic events, and finally take the natural logarithm to calculate the magnitude risk coefficient α. The formula is as follows.

[0047]

[0048] Where e is a natural constant. When the magnitude of the microseismic event detected this time is greater than or equal to 0, that is, M i When ≥0, it is high risk, and its risk coefficient α is specified i =100. When α i ≤e is low risk, and when 10≥α i >e is medium risk, when α i ≥10 indicates high risk.

[0049] Step 3: Establish a high-precision three-dimensional model of the underground gas storage geological body, and describe in detail the various factors that affect the sealing of the geological body, such as the overburden, blocking faults, closure overflow points, natural gas reservoirs, underlying supporting layers, as well as the spatial position of each wellbore, cementing quality, and casing quality.

[0050] Step 4: Project the microseismic events onto the 3D model and conduct correlation analysis between the microseismic frequent locations and the main fault / caprock weak zone / wellbore locations. Calculate the spatial position coordinates (X i , Y i , Z i ) and each fault plane, caprock weak zone, bottom support weak zone, oil and gas boundary, and wellbore, and the minimum value is L i .

[0051] Step 5: Calculate the weak point risk factor β for each microseismic event i .

[0052] β i =L i / R

[0053] The positioning error of the microseismic monitoring system is R. Generally, the spatial positioning accuracy of a specially deployed microseismic monitoring system is required to be between 5 and 20 meters. If the positioning error is too large, it will be difficult to effectively locate the location of the microseismic event.

[0054] When the distance between the earthquake source and the weak point is less than 5 times the spatial positioning accuracy, that is, β i ≤5 is high risk; when the distance between the earthquake source and the weak point is greater than 5 times and less than 10 times the spatial positioning accuracy, that is, 10≥β i When β>5, it is medium risk; when the distance between the earthquake source and the weak point is greater than 10 times the spatial positioning accuracy, and β i When >10, it is low risk.

[0055] At the same time, factors such as the strike, dip, and slip angle in the focal mechanism are considered. If the strike and dip are consistent with the strike and dip of the block fault, the risk coefficient of the weak point β i Go up a level.

[0056] Step 6: Calculate the relationship between microseismic events, gas injection and production volume, and formation pressure, and determine the frequency risk coefficient γ under the same gas injection and production conditions i .

[0057] First, the statistical unit needs to be determined. In the early stage of monitoring, due to limited monitoring data, one statistical unit can be 100,000 cubic meters / 2 MPa, that is, 0-100,000 cubic meters, 100,000-200,000 cubic meters, 200,000-300,000, ..., and so on; 8-10MPa, 10-12MPa, 12-14MPa, ..., and so on. After long-term monitoring, when there is a lot of monitoring data, the spacing of statistical units should be appropriately reduced, and one statistical unit can be 50,000 cubic meters / 1 MPa, that is, 0-50,000 cubic meters, 50,000-100,000 cubic meters, 100,000-150,000, ..., and so on; 8-9MPa, 9-10MPa, 10-11MPa, ..., and so on.

[0058] Then count each statistical unit in the database (similar injection and production volume Q i and formation pressure P i Under these conditions), the number of microseismic events per unit time is NS.

[0059] Finally, calculate the frequency risk coefficient γ i , determine the possible risks to the geological body under each gas injection and production volume or formation pressure condition.

[0060]

[0061] Where e is a natural constant, when γ i ≤e is low risk, and when 10≥α i >e is medium risk, when α i ≥10 indicates high risk.

[0062] Step 7: Comprehensively determine the geological body risk coefficient δ i .

[0063]

[0064] When δ i When it is greater than 50, it is a high risk and needs to be closely monitored. If necessary, the injection and production volume should be reduced. i When it is less than 50, it is medium-low risk.

[0065] Example 2

[0066] A method for early warning of risks in injection and production operation of a geological body of an underground gas storage reservoir, the method comprising the following steps:

[0067] Step 1: Use the microseismic monitoring system to record the time T of microseismic events in real time i , spatial position coordinates (X i , Y i , Z i ), magnitude M i , analyze the source mechanism (strike, dip, slip angle) and establish a microseismic event database. (See Table 1)

[0068] Table 1 includes a database of 20 microseismic events

[0069]

[0070]

[0071] Step 2: Read the total number of samples N in the database and the magnitude M of each microseismic event i , calculate the magnitude risk coefficient α of each microseismic event:

[0072]

[0073] e is a natural constant, when M i When ≥0, the risk factor α is high. i ≤e is low risk, and when 10≥α i >e is medium risk, when α i When ≥10, it is considered high risk. The calculation results are shown in Table 2

[0074] Table 2 Calculation results of magnitude risk coefficients of various microseismic events using the microseismic event database

[0075] Event count i Magnitude M Risk factor α Risk Level 1 -2 -2.70 Low risk 2 2 2.70 Low risk 3 0 0.00 Low risk 4 -2 -2.70 Low risk 5 -2 -2.70 Low risk 6 -2 -2.70 Low risk 7 0 0.00 Low risk 8 0 0.00 Low risk 9 -2 -2.70 Low risk 10 -1 -1.35 Low risk 11 -2 -2.70 Low risk 12 1 1.35 Low risk 13 2 2.70 Low risk 14 -1 -1.35 Low risk 15 2 2.70 Low risk 16 0 0.00 Low risk 17 0 0.00 Low risk 18 0 0.00 Low risk 19 0 0.00 Low risk 20 1 1.35 Low risk

[0076] Step 3: Establish a high-precision three-dimensional model of the underground gas storage geological body and project the microseismic events into the three-dimensional model.

[0077] Step 4: Carry out correlation analysis between the microseismic frequent locations and the main fault / caprock weak zone / wellbore location. Calculate the spatial position coordinates (Xi , Y i , Z i ) and the spatial distance L between the fault plane, the weak zone of the cap rock, the weak zone of the bottom support layer, the oil and gas boundary, and the wellbore i .

[0078] The table below takes the spatial distance between microseismic events and the wellbore as an example, and assumes that the direction and dip of the focal mechanism are inconsistent with the direction and dip of the block fault.

[0079] Table 3 Spatial distances between 20 microseismic events and the wellbore

[0080] Event count i Position X Position Y Position Z <![CDATA[Spatial distance L i > 1 434365.06 4571403.36 -1121.24 X2 Well 15 degrees 60 meters southeast 2 434815.34 4572120.44 -924.3 L4 well south west 45 degrees 50 meters 3 434325.08 4571420.51 -1164.69 X2 Well 40 degrees 50 meters north east 4 434739.09 4572075.37 -950.67 L4 Well 30 degrees 50 meters northwest 5 434401.88 4571487.55 -1202.02 X2 Well 20 degrees 10 meters southeast 6 434791.41 4572126.68 -947.71 L4 well south west 10 degrees 40 meters 7 434324.97 4571488.49 -1474.7 X2 Well 25 degrees 80 meters north east 8 434735.54 4572148.51 -1538.5 Well L4 35 degrees NW 90 meters 9 434399.22 4571453.46 -1491.12 X2 Well 15 degrees 60 meters southeast 10 434753.69 4572109.1 -1141.8 L4 well south west 45 degrees 50 meters 11 434414.96 4571425.81 -1602.55 X2 Well 40 degrees 50 meters north east 12 434814.33 4572066.84 -1194.34 L4 Well 30 degrees 50 meters northwest 13 434370.29 4571459.04 -1604.07 X2 Well 20 degrees 10 meters southeast 14 434775.21 4572150.75 -1478.52 L4 well south west 10 degrees 40 meters 15 434371.56 4571464.8 -1026.47 X2 Well 25 degrees 80 meters north east 16 434808.02 4572104.11 -1234.8 Well L4 35 degrees NW 90 meters 17 434379.22 4571428.14 -977.93 X2 Well 15 degrees 60 meters southeast 18 434789.68 4572107.36 -1013.55 L4 well south west 45 degrees 50 meters 19 434357.7 4571439.43 -1139.67 X2 Well 40 degrees 50 meters north east 20 434736.27 4572126.51 -1444.74 L4 Well 30 degrees 50 meters northwest

[0081] Step 5: Determine the positioning error of the microseismic monitoring system as R, and calculate the weak point risk coefficient β of each microseismic event i =L i / R, when β i ≤5 is high risk, and 10≥β i When β > 5, it is medium risk. i When it is greater than 10, it is a low risk. At the same time, factors such as the strike, dip, and slip angle in the focal mechanism are considered. If the strike and dip are consistent with the strike and dip of the block fault, the weak point risk coefficient β i Go up a level.

[0082] In this example, the positioning error is assumed to be 10, and the direction and dip of the focal mechanism are not consistent with the direction and dip of the block fault. Therefore, the risk coefficient of the weak point β i No need to increase the level, the calculation results are shown in Table 4

[0083] Table 4 includes the calculation results of the weak point risk coefficients of 20 microseismic events

[0084]

[0085]

[0086] Step 6: Calculate the frequency risk coefficient γ by the number of microseismic events NS per unit time under similar gas injection and production volume (deviation does not exceed 100,000 cubic meters / day) and formation pressure (deviation does not exceed 1MPa) i :

[0087]

[0088] Where e is a natural constant, when γ i ≤e is low risk, and when 10≥α i >e is medium risk, when α i ≥10 indicates high risk.

[0089] In the following table, forty units of microseismic frequency are used as an example to calculate the frequency risk coefficient and obtain the risk level per unit time. The example used and the calculation results are shown in Table 5.

[0090] Table 5 includes the number of microseismic events and the calculation results of frequency risk coefficient for 40 unit times

[0091]

[0092]

[0093]

[0094] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for early warning of injection and production operation of a gas storage geological body, characterized in that: The steps include: Step 1: Establish a microseismic event database; Step 2: Calculate the magnitude risk coefficient of each microseismic event; Step 3: Establish a high-precision three-dimensional model of the underground gas storage geological body; Step 4: Project the microseismic events into the 3D model and conduct correlation analysis; Step 5: Calculate the weak point risk factor of each microseismic event; Step 6: Calculate the frequency risk coefficient under the same gas injection and production conditions; Step 7: Comprehensively determine the risk factor of the geological body.

2. The method for early warning of injection and production operation of a gas storage reservoir geological body according to claim 1, characterized in that: Step 1: Using the microseismic monitoring system to record the time T of the microseismic event in real time i , spatial position coordinates (X i , Y i , Z i ), magnitude M i , analyze the source mechanism and establish a microseismic event database.

3. The method for early warning of injection and production operation of a gas storage reservoir geological body according to claim 2, characterized in that: Step 2: Read the total number of samples N in the database and the magnitude M of each microseismic event i , calculate the magnitude risk coefficient α of each microseismic event.

4. The method for early warning of injection and production operation of a gas storage geological body according to claim 3, characterized in that: The calculation method is as follows: first calculate the arithmetic mean of the magnitudes of all microseismic events that have occurred, then calculate the ratio of the magnitude of the current microseismic event to the arithmetic mean of the magnitudes of historical microseismic events, and finally take the natural logarithm to calculate the magnitude risk coefficient α. The formula is as follows: Where e is a natural constant. When the magnitude of the microseismic event detected this time is greater than or equal to 0, that is, M i When ≥0, it is high risk, and its risk coefficient α is specified i =100; When α i ≤e is low risk, and when 10≥α i >e is medium risk, when α i ≥10 indicates high risk.

5. The method for early warning of injection and production operation of a gas storage reservoir geological body according to claim 4, characterized in that: The step three is to establish a high-precision three-dimensional model of the underground gas storage geological body, describe the factors affecting the sealing of the geological body, such as the overburden, blocking faults, closure overflow points, natural gas reservoirs, and underlying supporting layers, as well as the spatial position of each wellbore, cementing quality, and casing quality.

6. The method for early warning of injection and production operation of a gas storage geological body according to claim 5, characterized in that: Step 4: Project the microseismic events onto the three-dimensional model, conduct correlation analysis between the microseismic frequent locations and the main fault / caprock weak zone / wellbore location; calculate the spatial position coordinates (X i , Y i , Z i ) and each fault plane, caprock weak zone, bottom support weak zone, oil and gas boundary, and wellbore, and the minimum value is L i .

7. The method for early warning of injection and production operation of a gas storage geological body according to claim 6, characterized in that: Step 5: Calculate the weak point risk coefficient β of each microseismic event i , b i =L i / R The positioning error of the microseismic monitoring system is R; When the distance between the earthquake source and the weak point is less than 5 times the spatial positioning accuracy, that is, β i ≤5 is high risk; when the distance between the earthquake source and the weak point is greater than 5 times and less than 10 times the spatial positioning accuracy, that is, 10≥β i When β>5, it is medium risk; when the distance between the earthquake source and the weak point is greater than 10 times the spatial positioning accuracy, and β i When >10, it is low risk.

8. The method for early warning of injection and production operation of a gas storage geological body according to claim 7, characterized in that: Step 6: Calculate the relationship between microseismic events and gas injection and production volume and formation pressure, and determine the frequency risk coefficient γ under the same gas injection and production conditions i .

9. The method for early warning of injection and production operation of a gas storage geological body according to claim 8, characterized in that: First, determine the statistical unit; Then count the number of microseismic events NS in each statistical unit in the database; Finally, calculate the frequency risk coefficient γ i , determine the risk to the geological body under each gas injection and production volume or formation pressure condition: Where e is a natural constant, when γ i ≤e is low risk, and when 10≥α i >e is medium risk, when α i ≥10 indicates high risk.

10. The method for early warning of injection and production operation of a gas storage geological body according to claim 9, characterized in that: Step 7: Comprehensively determine the geological body risk coefficient δ i : When δ i When it is greater than 50, it is a high risk, and the injection and production volume should be reduced; when δ i When it is less than 50, it is medium-low risk.

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