CN114925632A - Dynamic simulation method for fracture-cavity gas reservoir productivity test - Google Patents

Dynamic simulation method for fracture-cavity gas reservoir productivity test Download PDF

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CN114925632A
CN114925632A CN202210588914.9A CN202210588914A CN114925632A CN 114925632 A CN114925632 A CN 114925632A CN 202210588914 A CN202210588914 A CN 202210588914A CN 114925632 A CN114925632 A CN 114925632A
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well
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邹翔
黎隆兴
冉林
毛川勤
宁飞
朱斌
黄睿轩
廖凯
徐洁
谢孟珂
周宏�
吴洪波
魏明强
陈伟
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South China Oil And Gas Co Branch South China Gas Field Branch
Southwest Petroleum University
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Abstract

The invention discloses a dynamic simulation method for testing the productivity of a fracture-cavity type gas reservoir, which comprises the steps of designing and constructing a series fracture-cavity system according to parameters of a gas well of the fracture-cavity type gas reservoir; then, constructing a gas reservoir flowing mathematical model of the series fracture-cavity system based on a flowing model of the series fracture-cavity system, and representing the abnormal characteristic of linear reduction of bottom hole flowing pressure in the productivity test of the fracture-cavity type gas reservoir; and finally, establishing a three-parameter productivity equation considering the supply influence of the peripheral fracture and cave, and predicting the gas well productivity of the fracture and cave type gas reservoir and the peak regulation capacity of the gas well of the gas storage reservoir by using the three-parameter productivity equation. The invention provides a fracture-cave series model, which is used for establishing a mathematical model of gas reservoir flow of a fracture-cave system, and the computational simulation dynamics shows that the model represents abnormal characteristics in a fracture-cave gas reservoir productivity test; and a new energy production model considering the supply influence of the peripheral fracture holes is established, so that a simple and convenient method is provided for reasonably predicting the peak regulation capacity of the gas storage well.

Description

Dynamic simulation method for fracture-cavity gas reservoir productivity test
Technical Field
The invention relates to the technical field of petroleum and natural gas exploration, in particular to a dynamic simulation method for testing the productivity of a fracture-cavity type gas reservoir.
Background
The capacity of the fracture-cavity gas reservoir is high and is one of the preferable sites of the underground gas storage, but the heterogeneity of the fracture-cavity gas reservoir is extremely strong, and the connectivity of a fracture-cavity system influences the capacity of a gas well and the peak regulation capacity of the gas storage. The false phenomena of small reservoir capacity and high productivity are found in the productivity test process of the fracture-cavity gas reservoir: a considerable part of gas wells are unstable under a large-yield test, the flow pressure is linearly reduced, the recovery speed of the well closing pressure is low, and the final pressure is obviously lower than the initial pressure. It is conventionally understood that small production quantities result in a pressure drop in the formation, characteristic of a closed reservoir. Compared with the later injection and production dynamic discovery, the test data is evaluated by a conventional method, the predicted gas well yield is higher, and the actual running dynamic storage capacity is far larger than the storage capacity performance during the test, so that the question of high capacity and non-production is caused.
The space distribution of the fracture-cave system is complex, the diversion capacity of the karst cave is extremely high, the flow pressure drop in the karst cave can be ignored, the flow pressure drop of the fracture-cave system is mainly consumed in the cracks connected with the karst cave, and the flow diversion capacity of the cracks on the main runner determines the capacity of the gas well.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a dynamic simulation method for a fracture-cavity gas reservoir productivity test.
The purpose of the invention is realized by the following technical scheme:
a dynamic simulation method for a fracture-cavity gas reservoir productivity test comprises the following steps:
s1, designing and constructing a series connection fracture-cave system according to the parameters of the fracture-cave gas reservoir gas well;
s2, constructing a fracture-cavity system gas reservoir flow mathematical model based on the flow model of the series fracture-cavity system, and representing the abnormal characteristic of linear reduction of bottom hole flowing pressure in the fracture-cavity gas reservoir productivity test;
and S3, establishing a three-parameter productivity equation considering the supply influence of the peripheral fracture and cave, and predicting the productivity of the fracture and cave gas reservoir well and the peak regulation capacity of the gas reservoir well by using the three-parameter productivity equation.
Specifically, the step S1 specifically includes: based on gas well parameters in the fracture-cavity type gas reservoir, a fracture-cavity system communicated with the gas well is divided into a near-well unit and a peripheral unit, and a macroscopic flow model of the series fracture-cavity system is constructed. Then, describing the flow pressure drop relation of the slot-hole system, and specifically comprising the following sub-steps of:
s101, describing the flowing pressure drop of the near-well unit to the well bore by using a binomial relation:
p 1 2 -p wf 2 ＝Aq 1 +Bq 1 2
wherein p is 1 Formation pressure, p, of the near-well unit wf Bottom hole flow pressure, A, B productivity factor; q. q.s 1 A test flow for a gas well; and S102, describing the flow pressure drop between the near-well unit and the peripheral unit by using a linear relation:
p 2 2 -p 1 2 ＝Cq 2
wherein p is 2 Is the formation pressure of the peripheral unit, and C is the productivity coefficient of the peripheral unit; q. q.s 2 For the flow between the near-well unit and the peripheral unit, q 2 For the make-up flow.
Specifically, the step S2 specifically includes the following sub-steps:
s201: forming a material balance equation by using the accumulated yield of the near-well unit and the peripheral unit to form a change relation of the formation pressure of the near-well unit and the peripheral unit, and constructing a mathematical model of the gas reservoir flow of the series fracture-cave system;
s202: according to the gas reservoir flow mathematical model of the series-connection fracture-cave system, the simulation pressure and the yield dynamic are calculated through a numerical solution method, and the abnormal characteristics in the fracture-cave type gas reservoir productivity test are represented.
Specifically, the substep S201 specifically includes:
the change relation of the formation pressure of the near well unit is
Figure BDA0003664273060000021
The change relation of the formation pressure of the peripheral unit is
Figure BDA0003664273060000022
Wherein p is i Initial formation pressure of the fracture-cave system, G 1 Reservoir capacity of near-well units, G 2 Is the library capacity of the peripheral unit, t is the test time;
respectively deriving the formation pressure of the peripheral unit and the near-well unit to construct a mathematical model of the gas reservoir flowing of the series fracture-cavity system:
Figure BDA0003664273060000023
Figure BDA0003664273060000024
specifically, the substep S202 specifically includes: solving the model in a numerical mode, and discretizing the model in a step-by-step implicit difference format:
Figure BDA0003664273060000025
Figure BDA0003664273060000026
wherein, Δ t is a time step, subscript n represents a current time step, and n +1 represents a next time step to be solved; in the initial state: n is 0, p 1,0 ＝p i ，p 2,0 ＝p i ；
Expanding and organizing the expression obtained by the dispersion into
Figure BDA0003664273060000031
Figure BDA0003664273060000032
Get
Figure BDA0003664273060000033
Figure BDA0003664273060000034
2 quadratic equations are formed:
a 1 p 1,n+1 2 +p 1,n+1 +c 1 ＝0
a 2 p 2,n+1 2 +p 2,n+1 +c 2 ＝0
according to the test flow q 1 According to the sequence of flow influence, the near-well single-formation pressure p is solved first 1,n+1 Then solving the formation pressure p of the peripheral unit 2,n+1 ：
Figure BDA0003664273060000035
Figure BDA0003664273060000036
Calculating the bottom hole flowing pressure p according to the solved near well single formation pressure and the periphery unit formation pressure wf And a make-up flow q 2 ：
p wf 2 ＝p 1,n+1 2 -(Aq 1 +Bq 1 2 )
Figure BDA0003664273060000037
Specifically, the step S3 specifically includes; according to the flow pressure drop from the near-well unit to the shaft and the flow pressure drop between the near-well unit and the peripheral unit in the productivity test, establishing a new productivity model considering the replenishment influence of the peripheral fracture hole:
p 2 2 -p wf 2 ＝Aq 1 +Cq 2 +Bq 1 2
when steady state flow is formed q 2 ≈q 1 When the reservoir volume of the peripheral unit is much larger than the near-well unit, the pressure p of the peripheral unit 2 Formation pressure p corresponding to series-wound fracture-cave system r Obtaining a binomial capacity equation of the series-connection seam hole system, which is called as a system capacity equation:
p r 2 -p wf 2 ＝(A+C)q 1 +Bq 1 2
and evaluating the productivity of the fracture-cavity gas reservoir gas well by using a system productivity equation, and predicting the peak regulation capacity of the gas reservoir well.
The invention has the beneficial effects that: aiming at the abnormal testing mechanism that part of gas wells are unstable under a large-yield test, the flowing pressure is linearly reduced, the recovery speed of the well closing pressure is low, and the end point pressure is obviously lower than the initial pressure in the capacity test of the fracture-cavity gas reservoir, the invention provides a fracture-cavity series model, establishes a fracture-cavity system gas reservoir flowing mathematical model, and calculates and simulates dynamic states to show that the model represents abnormal characteristics in the capacity test of the fracture-cavity gas reservoir; and a new energy production model considering the supply influence of the peripheral fracture holes is established, so that a simple and convenient method is provided for reasonably predicting the peak regulation capacity of the gas storage well.
Drawings
FIG. 1 is a flow chart of the method of the present invention
FIG. 2 is a schematic view of the tandem slot and hole system of the present invention;
FIG. 3 is a simulation plot of a short time system well test;
FIG. 4 is a long-term system well testing simulation graph;
FIG. 5 is a graph comparing inflow curves for a long test with a system;
fig. 6 is an inflow curve of the system compared to a short time test.
Detailed Description
The following detailed description will be selected to more clearly understand the technical features, objects and advantages of the present invention. It should be understood that the embodiments described are illustrative of some, but not all embodiments of the invention, and are not to be construed as limiting the scope of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step, based on the embodiments of the present invention, belong to the scope of protection of the present invention.
The capacity of the fracture-cavity gas reservoir is high and is one of the preferable sites of the underground gas storage, but the heterogeneity of the fracture-cavity gas reservoir is extremely strong, and the connectivity of a fracture-cavity system influences the capacity of a gas well and the peak regulation capacity of the gas storage. In the productivity test process of the fracture-cavity gas reservoir, a considerable part of gas wells are not stable under a large-yield test, the flow pressure is linearly reduced, the recovery speed of the shut-in pressure is low, and the final pressure is obviously lower than the initial pressure. Aiming at the mechanism of the test abnormality, a fracture-cavity series model is provided, a fracture-cavity system gas reservoir flow mathematical model is established, and the calculation simulation dynamics shows that the model represents the abnormal characteristics in the fracture-cavity gas reservoir productivity test; and a new energy production model considering the supply influence of the peripheral seam holes is established, and a simple method is provided for reasonably predicting the peak regulation capacity of the gas storage well. The specific implementation of the process is given in the examples below.
The first embodiment is as follows:
in this embodiment, as shown in fig. 1, a dynamic simulation method for a fracture-cavity gas reservoir productivity test mainly includes the following steps: s1, designing and constructing a series fracture-cave system according to parameters of the fracture-cave gas reservoir gas well;
s2, constructing a fracture-cavity system gas reservoir flow mathematical model based on the series fracture-cavity system flow model, and representing the abnormal characteristic of linear reduction of bottom hole flow pressure in the fracture-cavity gas reservoir productivity test;
and S3, establishing a three-parameter productivity equation considering the supply influence of the peripheral fracture and cave, and predicting the productivity of the fracture and cave gas reservoir well and the peak regulation capacity of the gas reservoir well by using the three-parameter productivity equation.
In this embodiment, the detailed implementation process of the method is as follows:
1. physical model
For simplicity, as shown in fig. 2, the present embodiment divides the gas well connected fracture-cavity system into 2 units: the flow conductivity between the units is smaller than that in the units, so that a macroscopic series system is formed. If the reservoir capacity of the near-well unit is small and the reservoir capacity of the peripheral unit is large, the formation pressure of the near-well unit is remarkably reduced under the constant high-yield production test condition, and the characteristics of linear reduction of bottom hole flowing pressure and low shut-in pressure are presented.
2. Mathematical model
Setting: gas well test flow rate of q 1 Bottom hole flowing pressure p wf Initial formation pressure of the fracture-cave system is p i Reservoir volume of near well unit is G 1 Pressure p 1 The library capacity of the peripheral unit is G 2 Pressure p 2 With flow between units of q 2 Balance q 2 Is the supply flow.
In the productivity test process, the near well zone has large pressure drop and high flow speed, and the flow pressure drop from the near well unit to the shaft is described by a binomial relation:
p 1 2 -p wf 2 ＝Aq 1 +Bq 1 2 (1)
wherein p is wf For bottom hole flow pressure, A, B is the productivity factor.
The flow pressure drop between the near-well unit and the peripheral unit is described in a linear relationship:
p 2 2 -p 1 2 ＝Cq 2 (2)
wherein C is the capacity coefficient of the peripheral unit.
Cumulative production of the near well unit is
Figure BDA0003664273060000051
Cumulative throughput of peripheral units of
Figure BDA0003664273060000052
Wherein t is the test time.
Determining the formation pressure change of the cell from the gas reservoir material balance equation:
Figure BDA0003664273060000053
Figure BDA0003664273060000054
wherein z is a deviation factor of natural gas, subscript i corresponds to an initial formation pressure condition, and subscripts 1 and 2 correspond to a near well and a peripheral unit respectively.
The total produced quantity in the test process is small, and the change of the formation pressure is not large. When the pressure varies by a small magnitude, z is approximately constant, and the formation pressure of a cell can be simplified as:
Figure BDA0003664273060000055
Figure BDA0003664273060000056
and (3) obtaining a mathematical model of the unit pressure change by differentiating the time t in the formulas (7) and (8):
Figure BDA0003664273060000061
Figure BDA0003664273060000062
solving in a numerical way, discretizing equations (9) and (10) in a step-by-step implicit difference format:
Figure BDA0003664273060000063
Figure BDA0003664273060000064
where Δ t is the time step, subscript n represents the current time step, and n +1 represents the next time step to be solved. In the initial state: n is 0, p 1,0 ＝p i ，p 2,0 ＝p i 。
Unfolding and arranging the formulas (11) and (12) into
Figure BDA0003664273060000065
Figure BDA0003664273060000066
Get
Figure BDA0003664273060000067
Figure BDA0003664273060000068
2 quadratic equations are formed:
a 1 p 1,n+1 2 +p 1,n+1 +c 1 ＝0 (17)
a 2 p 2,n+1 2 +p 2,n+1 +c 2 ＝0 (18)
according to the test flow q 1 According to the sequence of flow influence, the near-well unit pressure p is solved first 1,n+1 Then peripheral cell pressure p is solved 2,n+1 ：
Figure BDA0003664273060000069
Figure BDA00036642730600000610
Then calculating the bottom hole flow pressure p by the formula (21) wf Calculating the supply flow q by the formula (22) 2 ：
p wf 2 ＝p 1,n+1 2 -(Aq 1 +Bq 1 2 ) (21)
Figure BDA00036642730600000611
3. Productivity model
Substituting formula (2) into formula (1) to obtain
p 2 2 -p wf 2 ＝Aq 1 +Cq 2 +Bq 1 2 (23)
When steady state flow is formed q 2 ≈q 1 When the reservoir volume of the peripheral unit is much larger than the near-well unit, the pressure p of the peripheral unit 2 Formation pressure p corresponding to series-wound fracture-cave system r Obtaining a binomial productivity equation of the series-connection slotted hole system, which is called as a system productivity equation:
p r 2 -p wf 2 ＝(A+C)q 1 +Bq 1 2 (24)
4. computing case
Parameters for a series-connected fracture-cavity system are shown in table 1, and a test plan for well testing of the system: one working system every 4 hours, the yield sequence is 70 multiplied by 10 4 m 3 /d、100×10 4 m 3 /d、130×10 4 m 3 /d、160×10 4 m 3 And d. The simulated well test curve calculated by the method is shown in figure 3, and the bottom hole flow pressure keeps linearly decreasing in the flowing test period, the well shut-in recovery pressure is lower than the initial pressure, and the supply flow q is noticed 2 The replenishment flow rate of the peripheral units under short-time testing is much less than the test throughput as the differential pressure between the units increases.
TABLE 1 tandem Slot coefficient parameters
Figure BDA0003664273060000071
The simulation curve of the production well testing with 1 day of each working system time is shown in FIG. 4, and it can be seen that the replenishment flow q is increased with the expansion of the pressure difference between the units 2 Gradually increased when the supply flow q is increased 2 Approach to test yield q 1 In time, the descending trend of the bottom hole flow pressure becomes slow, and the pressure yield relation reflects the integral production capacity of the series connection fracture-cavity system.
5. Capacity comparison
Corresponding to the simulation schemes of fig. 2 and 3, the calculated flow pressure at the end of each working system is shown in table 2, and the analysis result according to the conventional binomial formula is shown in table 3. The comparison shows that whether the test is a short-time test or a long-time test, the value A obtained by the conventional analysis method is small, the value B is large, and the coefficient B value describing the high-speed turbulent flow pressure drop is opposite to the unimpeded flow Q AOF Extremely sensitive and evaluated unimpeded flow Q AOF Are all smaller than the theoretical value of a slotted-hole system.
TABLE 2 analog calculation of streaming pressure for short and long term testing
Figure BDA0003664273060000072
TABLE 3 Productivity analysis results
Figure BDA0003664273060000081
For example, as shown in fig. 5 and 6, when the productivity of the long-term test and the productivity of the short-term test under different pressures are compared with the inflow curve predicted by the system productivity, it can be seen that in the practical range of several MPa production pressure difference, the productivity of the long-term test is close to the productivity of the system, the productivity of the short-term test is higher and is aggravated along with the decrease of the pressure of the ground, and the peak shaving capacity of the gas well of the gas storage reservoir is exaggerated by designing according to the productivity of the short-term test.
The strength of the supply among the units controls the time for entering stable flow, the larger the C value is, the weaker the supply is, the longer the time for entering stable flow is, but the long-time capacity test is not practical.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, and such changes and modifications are within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (6)

1. A dynamic simulation method for a fracture-cavity gas reservoir productivity test is characterized by comprising the following steps:
s1, designing and constructing a flow model of the series fracture-cavity system according to parameters of the fracture-cavity type gas reservoir and the gas well;
s2, constructing a mathematical model of gas reservoir flow of the series fracture-cavity system based on the flow model of the series fracture-cavity system, and representing the abnormal characteristic of linear reduction of bottom hole flowing pressure in the fracture-cavity type gas reservoir productivity test;
and S3, establishing a three-parameter productivity equation considering the influence of peripheral fracture hole supply, and predicting the gas well productivity of the fracture-cavity gas reservoir and the peak shaving capacity of the gas well of the gas storage reservoir by using the three-parameter productivity equation.
2. The method of claim 1, wherein the step S1 comprises: dividing a fracture-cave system communicated with a gas well into a near well unit and a peripheral unit based on gas well parameters in a fracture-cave gas reservoir, and constructing a macroscopic flow model of a series fracture-cave system; describing the flow pressure drop relationship of the fracture-cavity system, and specifically comprising the following sub-steps of:
s101, describing the flowing pressure drop of the near-well unit to the well bore by using a binomial relation:
p 1 2 -p wf 2 ＝Aq 1 +Bq 1 2
wherein p is 1 Formation pressure, p, of the near-well unit wf Bottom hole flow pressure, A, B productivity factor; q. q.s 1 Is the test flow rate of the gas well; and S102, describing the flow pressure drop between the near-well unit and the peripheral unit by using a linear relation:
p 2 2 -p 1 2 ＝Cq 2
wherein p is 2 Is the formation pressure of the peripheral unit, and C is the productivity coefficient of the peripheral unit; q. q.s 2 For the flow between the near-well unit and the peripheral unit, q 2 For the make-up flow.
3. The method as claimed in claim 1, wherein the step S2 comprises the following steps:
s201: forming a material balance equation by using the accumulated yield of the near-well unit and the peripheral unit to form a change relation of the formation pressure of the near-well unit and the peripheral unit, and constructing a mathematical model of the gas reservoir flow of the series fracture-cave system;
s202: according to the gas reservoir flow mathematical model of the series-connection fracture-cave system, the simulation pressure and the yield dynamic are calculated through a numerical solution method, and the abnormal characteristics in the fracture-cave gas reservoir productivity test process are represented.
4. The method as claimed in claim 3, wherein the substep S201 comprises:
the change relationship of the formation pressure of the near well unit is
Figure FDA0003664273050000011
The change relation of the formation pressure of the peripheral unit is
Figure FDA0003664273050000012
Wherein p is i Initial formation pressure of the fracture-cave system, G 1 Reservoir capacity of near-well units, G 2 Is the library capacity of the peripheral unit, t is the test time;
respectively deriving the formation pressure of the peripheral unit and the near-well unit to construct a mathematical model of the gas reservoir flow of the series fracture-cavity system:
Figure FDA0003664273050000021
Figure FDA0003664273050000022
5. the method according to claim 3, wherein the substep S202 comprises:
solving the model in a numerical mode, and discretizing the model in a step-by-step implicit difference format:
Figure FDA0003664273050000023
Figure FDA0003664273050000024
wherein, Δ t is a time step, subscript n represents a current time step, and n +1 represents a next time step to be solved; in the initial state: n is 0, p 1，0 ＝p i ，p 2，0 ＝p i ；
Expanding and organizing the expression obtained by the dispersion into
Figure FDA0003664273050000025
Figure FDA0003664273050000026
Get
Figure FDA0003664273050000027
Figure FDA0003664273050000028
2 quadratic equations are formed:
a 1 p 1，n+1 2 +p 1，n+1 +c 1 ＝0
a 2 p 2，n+1 2 +p 2，n+1 +c 2 ＝0
according to the test flow q 1 According to the sequence of flow influence, the near-well single-formation pressure p is solved first 1，n+1 Then the formation pressure p of the peripheral unit is solved 2，n+1 ：
Figure FDA0003664273050000029
Figure FDA00036642730500000210
Calculating the bottom hole flowing pressure p according to the solved near well single formation pressure and the periphery unit formation pressure wf And a make-up flow q 2 ：
p wf 2 ＝p 1，n+1 2 -(Aq 1 +Bq 1 2 )
Figure FDA0003664273050000031
6. The method of claim 1, wherein the step S3 comprises; according to the flow pressure drop from the near-well unit to the shaft and the flow pressure drop between the near-well unit and the peripheral unit in the productivity test, establishing a new productivity model considering the replenishment influence of the peripheral fracture hole:
p 2 2 -p wf 2 ＝Aq 1 +Cq 2 +Bq 1 2
when steady state flow is formed q 2 ≈q 1 When the reservoir volume of the peripheral unit is much larger than the near-well unit, the pressure p of the peripheral unit 2 Formation pressure p corresponding to series-wound fracture-cave system r Obtaining a binomial productivity equation of the series-connection slotted hole system, which is called as a system productivity equation:
p r 2 -p wf 2 ＝(A+C)q 1 +Bq 1 2
and evaluating the productivity of the fracture-cave gas reservoir gas well by using a system productivity equation, and predicting the peak regulation capacity of the gas reservoir well.
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Citations (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002088522A1 (en) * 2001-04-25 2002-11-07 Halliburton Energy Services, Inc. Method, system and tool for reservoir evaluation and well testing during drilling operations
US20130041633A1 (en) * 2011-08-11 2013-02-14 Conocophillips Company Heat front capture in thermal recovery simulations of hydrocarbon reservoirs
CN104331745A (en) * 2014-10-17 2015-02-04 成都理工大学 Period-divided and reason-divided prediction evaluation method of natural fracture in gas reservoir
WO2016192077A1 (en) * 2015-06-04 2016-12-08 中国石油集团川庆钻探工程有限公司长庆井下技术作业公司 Method for establishing and solving numerical well-testing model of horizontal well for tight gas hydraulic fracturing
CN106250664A (en) * 2015-06-12 2016-12-21 中国石油天然气股份有限公司 The Forecasting Methodology of low hole Fractured sandstone reservoirs production capacity and device
CN107563027A (en) * 2017-08-21 2018-01-09 西南石油大学 For analyzing the WELL TEST INTERPRETATION MODEL and method of more fracture-cavity units cascaded structures
CN108798634A (en) * 2018-07-09 2018-11-13 合肥辰工科技有限公司 A kind of fractured-vuggy reservoir list hole-mean value of single layer Well Test Data Analysis Method
CN110532592A (en) * 2019-07-15 2019-12-03 西南石油大学 A kind of fracture hole oil-gas reservoir fractured well cavern Well Test Data Analysis Method
CN110593865A (en) * 2019-09-29 2019-12-20 中国石油集团川庆钻探工程有限公司 Well testing interpretation method for characteristic parameters of oil reservoir fracture hole
CN110984973A (en) * 2019-11-29 2020-04-10 中国石油集团川庆钻探工程有限公司 Determination method for single-well controlled reserve of fracture-cave carbonate gas reservoir
AU2020100337A4 (en) * 2020-01-09 2020-04-16 China University Of Geosciences, Beijing Method and system for generating unsteady-state well test chart of highly-deviated well in gas reservoir
CN111581786A (en) * 2020-04-19 2020-08-25 东北石油大学 Well testing interpretation model for analyzing fracture-cave series-connection mode double-hole composite reservoir
WO2020216313A1 (en) * 2019-04-26 2020-10-29 西南石油大学 Modeling method and storage medium of fractured-vuggy series reservoir single-well pressure prediction model
US20210003731A1 (en) * 2019-07-04 2021-01-07 Chengdu University Of Technology Method for determining favorable time window of infill well in unconventional oil and gas reservoir
AU2020103953A4 (en) * 2020-12-08 2021-02-11 Southwest Petroleum University Method and system for predicting production of fractured horizontal well in shale gas reservoir
CN113626967A (en) * 2020-05-07 2021-11-09 中国石油化工股份有限公司 Fracture-cavity reservoir productivity determination method and system considering stress sensitivity
CN113627638A (en) * 2020-05-07 2021-11-09 中国石油化工股份有限公司 Fracture-cavity reservoir productivity determination method and system considering starting pressure
CN113627068A (en) * 2020-05-07 2021-11-09 中国石油化工股份有限公司 Method and system for predicting well testing productivity of fracture-cavity type oil and gas reservoir
CN113792479A (en) * 2021-08-23 2021-12-14 北京科技大学 Physical constraint-based coalbed methane reservoir fracturing effect evaluation method
CN113868824A (en) * 2020-06-30 2021-12-31 中国石油化工股份有限公司 Prediction method and system for shale gas pressure post-transformation seam network
CN114427445A (en) * 2020-09-11 2022-05-03 中国石油化工股份有限公司 Method and system for calculating infinite stratum dynamic capacity of fracture-cavity oil reservoir

Patent Citations (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002088522A1 (en) * 2001-04-25 2002-11-07 Halliburton Energy Services, Inc. Method, system and tool for reservoir evaluation and well testing during drilling operations
US20130041633A1 (en) * 2011-08-11 2013-02-14 Conocophillips Company Heat front capture in thermal recovery simulations of hydrocarbon reservoirs
CN104331745A (en) * 2014-10-17 2015-02-04 成都理工大学 Period-divided and reason-divided prediction evaluation method of natural fracture in gas reservoir
WO2016192077A1 (en) * 2015-06-04 2016-12-08 中国石油集团川庆钻探工程有限公司长庆井下技术作业公司 Method for establishing and solving numerical well-testing model of horizontal well for tight gas hydraulic fracturing
CN106250664A (en) * 2015-06-12 2016-12-21 中国石油天然气股份有限公司 The Forecasting Methodology of low hole Fractured sandstone reservoirs production capacity and device
CN107563027A (en) * 2017-08-21 2018-01-09 西南石油大学 For analyzing the WELL TEST INTERPRETATION MODEL and method of more fracture-cavity units cascaded structures
CN108798634A (en) * 2018-07-09 2018-11-13 合肥辰工科技有限公司 A kind of fractured-vuggy reservoir list hole-mean value of single layer Well Test Data Analysis Method
WO2020216313A1 (en) * 2019-04-26 2020-10-29 西南石油大学 Modeling method and storage medium of fractured-vuggy series reservoir single-well pressure prediction model
US20210003731A1 (en) * 2019-07-04 2021-01-07 Chengdu University Of Technology Method for determining favorable time window of infill well in unconventional oil and gas reservoir
CN110532592A (en) * 2019-07-15 2019-12-03 西南石油大学 A kind of fracture hole oil-gas reservoir fractured well cavern Well Test Data Analysis Method
CN110593865A (en) * 2019-09-29 2019-12-20 中国石油集团川庆钻探工程有限公司 Well testing interpretation method for characteristic parameters of oil reservoir fracture hole
CN110984973A (en) * 2019-11-29 2020-04-10 中国石油集团川庆钻探工程有限公司 Determination method for single-well controlled reserve of fracture-cave carbonate gas reservoir
AU2020100337A4 (en) * 2020-01-09 2020-04-16 China University Of Geosciences, Beijing Method and system for generating unsteady-state well test chart of highly-deviated well in gas reservoir
CN111581786A (en) * 2020-04-19 2020-08-25 东北石油大学 Well testing interpretation model for analyzing fracture-cave series-connection mode double-hole composite reservoir
CN113626967A (en) * 2020-05-07 2021-11-09 中国石油化工股份有限公司 Fracture-cavity reservoir productivity determination method and system considering stress sensitivity
CN113627638A (en) * 2020-05-07 2021-11-09 中国石油化工股份有限公司 Fracture-cavity reservoir productivity determination method and system considering starting pressure
CN113627068A (en) * 2020-05-07 2021-11-09 中国石油化工股份有限公司 Method and system for predicting well testing productivity of fracture-cavity type oil and gas reservoir
CN113868824A (en) * 2020-06-30 2021-12-31 中国石油化工股份有限公司 Prediction method and system for shale gas pressure post-transformation seam network
CN114427445A (en) * 2020-09-11 2022-05-03 中国石油化工股份有限公司 Method and system for calculating infinite stratum dynamic capacity of fracture-cavity oil reservoir
AU2020103953A4 (en) * 2020-12-08 2021-02-11 Southwest Petroleum University Method and system for predicting production of fractured horizontal well in shale gas reservoir
CN113792479A (en) * 2021-08-23 2021-12-14 北京科技大学 Physical constraint-based coalbed methane reservoir fracturing effect evaluation method

Non-Patent Citations (7)

* Cited by examiner, † Cited by third party
Title
LU WANG ET AL.: "Pore structure characteristics of an ultradeep carbonate gas reservoir and their effects on gas storage and percolation capacities in the Deng IV member, Gaoshiti-Moxi Area, Sichuan Basin, SW China", 《MARINE AND PETROLEUM GEOLOGY》, vol. 111, no. 1, pages 44 - 65, XP085899086, DOI: 10.1016/j.marpetgeo.2019.08.012 *
刘荣和等: "裂缝-孔隙型碳酸盐岩气藏稳态产能评价方法", 《特种油气藏》, vol. 29, no. 2 *
李勇明;罗剑;郭建春;赵金洲;: "介质变形和长期导流裂缝性气藏压裂产能模拟研究", 天然气工业, no. 09 *
聂权;段希宇;唐愈轩;魏明强;郭富风;李安豪;陈伟华;: "缝洞型碳酸盐岩气藏的单井试采配产方法研究――以高石梯灯四气藏为例", 重庆科技学院学报(自然科学版), no. 05 *
贾虎;蒲万芬;廖然;袁成东;汤柏松;赵若锟;: "缝洞型油气藏物理模拟试验方法研究", 石油钻探技术, no. 06 *
门成全;张岐;何顺利;: "碳酸盐岩缝洞型气藏的水平井动态预测模型", 科学技术与工程, no. 17 *
陈冀嵋;徐乐;: "考虑裂缝壁面蚓孔区影响的酸压井产能预测", 天然气工业, no. 07 *

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