CN113919240A - High-pressure gas reservoir parameter calculation method based on oil and gas well production data - Google Patents
High-pressure gas reservoir parameter calculation method based on oil and gas well production data Download PDFInfo
- Publication number
- CN113919240A CN113919240A CN202010644070.6A CN202010644070A CN113919240A CN 113919240 A CN113919240 A CN 113919240A CN 202010644070 A CN202010644070 A CN 202010644070A CN 113919240 A CN113919240 A CN 113919240A
- Authority
- CN
- China
- Prior art keywords
- pressure
- flow
- well
- flow field
- reservoir
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Abstract
The invention discloses a method for calculating high-pressure gas reservoir parameters based on oil-gas well production data, belonging to the technical field of oil and gas exploitation, analyzing the pressure derivative change of the flow field evolution of the reservoir model to obtain the pressure derivative change rule of the formation flow field evolution, according to the data of the pressure derivative change rule, applying flow normalized pressure RNP analysis, according to the analyzed data, applying an RNP method to draw a log-log curve, identifying flow field characteristics similar to those in a pressure drop test, fitting a theoretical plate with the log-log curve, identifying the type of a formation flow field, the invention provides an effective well testing analysis method and a reservoir parameter testing means for the oil and gas well without pressure recovery data and with violent flow change, and has important significance for the understanding of the reservoir properties of the high-pressure gas reservoir and the dynamic well testing of the oil and gas well production.
Description
Technical Field
The invention relates to the technical field of petroleum and natural oil and gas exploitation, in particular to a high-pressure gas reservoir parameter evaluation method based on oil and gas well long-term production data.
Background
The high-temperature high-pressure acid gas reservoir of the Chinese petrochemical industry mainly comprises blocks such as plain, Yuan-Ba, Chuanxi and the like. 2013, the SN4 well obtains the daily yield of 40 multiplied by 104m through the test of the lower section of the eagle mountain group3The high-yield industrial airflow marks that SN regions have wide exploration and development prospects and is an important strategic position for exploration and development of medium petrochemical natural gas.
The depth of the ordinary light and the West well is about 5000 meters, which is shallower than that of the SN well region; the well depth of the meta-dam block is close to that of the SN, but the well formation temperature of the meta-dam is 145 ℃, the formation pressure is about 67MPa, and the well pressure of the SN well area is higher (the original formation pressure is 78.8MPa/6676m) and the temperature is higher (the formation temperature is 191.81 ℃/6676 m). Therefore, the SN well area has the following problems when the traditional well test interpretation and productivity evaluation are applied:
1) the pressure is high, the temperature is high for well head pressure receives the temperature influence more seriously, and well head pressure fluctuation range is bigger, carries out well head pressure and more difficult when to the shaft bottom pressure conversion.
2) The reservoir is a carbonate reservoir, the seepage storage space comprises caves, erosion holes and cracks, and the model selection difficulty is high when well testing interpretation is carried out.
3) The gas reservoir contains CO2Contains a little of H2S, calculating physical parameters of the gas is different from that of the conventional gas, and the influence of the acid gas is considered when well testing interpretation is carried out.
4) SN well zone currently in exploration phase, only 3 pilot production wells, of which only SN is4The well completes the pressure recovery test and the system test, the gas well production time is short, and the reference data is few.
Disclosure of Invention
The embodiment of the invention provides a method for calculating reservoir parameters of a high-pressure gas reservoir based on production data of an oil-gas well. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
The invention provides a high-pressure gas reservoir parameter evaluation method based on oil and gas well long-term production data, aiming at overcoming the problems in the traditional well testing interpretation and productivity evaluation. The technology can be applied to similar high-temperature and high-pressure gas reservoirs, is also suitable for conventional gas reservoirs, and improves the interpretation precision of test data; the reservoir stratum and the evaluation measure effects can be effectively known, a basis is provided for later development and economic evaluation, and the method has wide popularization and application prospects and good economic benefit and social benefit prediction.
Another objective of the present invention is to provide a method for evaluating parameters of a high-Pressure gas reservoir based on long-term production data of an oil and gas well, which is not required to perform a well shut-in test, but is based on long-term production data, and performs a normalization process on complex dynamic production data by introducing a flow-Normalized Pressure RNP (Rate-Normalized Pressure) analysis method, so as to integrate a set of long-term complex production data into a normal production Pressure drop behavior equivalent to the complex production data, and identify flow field characteristics similar to those in the Pressure drop test by using an RNP log-log curve, so as to obtain important reservoir parameters such as permeability, skin coefficient, fracture conductivity, leakage flow volume, Pressure recovery constant Pressure boundary, and RNP constant Pressure boundary of a formation.
According to the embodiment of the invention, a method for calculating reservoir parameters of a high-pressure gas reservoir based on production data of an oil and gas well is provided, which comprises the following steps:
s1: analyzing the pressure derivative change of the flow field evolution of the reservoir model to obtain the pressure derivative change rule of the formation flow field evolution;
s2: collecting production data by applying flow normalized pressure (RNP) analysis according to pressure derivative change rule data of the formation flow field evolution of S1, and integrating the production data into equivalent constant unit production pressure drop behavior data;
s3: according to the data analyzed in the S2, drawing a double-logarithm curve by applying the RNP method, and identifying flow field characteristics similar to those in a pressure drop test;
s4: fitting a theoretical plate with the double logarithmic curve of S3 to identify the type of the formation flow field;
s5: and calculating different flow pattern stages to obtain reservoir parameters based on the stratum flow field type of S4.
Preferably, the reservoir parameters obtained by calculating the different flow pattern stages specifically include permeability and skin coefficient, fracture conductivity, leakage flow volume, pressure recovery pressure boundary and RNP pressure boundary.
Preferably, the reservoir model comprises a straight well homogeneous circular stratum, a straight well homogeneous rectangular stratum (central well), a straight well homogeneous rectangular stratum (single-sided well), a fractured straight well homogeneous stratum, a straight well natural fracture stratum and a horizontal well homogeneous stratum, and also comprises a combination form of the common oil and gas well and the reservoir model.
Preferably, the pressure derivative variation analysis has different forms of evolution for different reservoirs,
the vertical well homogeneous circular formation flow field evolution comprises a shaft reservoir effect, near well radial flow analysis and boundary effect analysis;
the vertical well homogeneous rectangular stratum (central well) flow field evolution comprises a shaft reservoir effect, a near well radial flow analysis, a boundary effect and a river linear flow analysis;
the flow field evolution of the vertical homogeneous rectangular stratum (single-sided well) comprises near-well radial flow analysis, single-sided boundary effect response, boundary effect and river linear flow analysis;
the evolution of a flow field of a homogeneous rectangular stratum of a fracturing vertical well comprises linear flow in a crack, model flow of a vertical crack steamed dumpling in a linear flowing dry reservoir in the crack, pseudo radial flow of a ring crack and linear flow of the reservoir perpendicular to the crack surface;
the flow field evolution of the vertical well natural fracture stratum comprises radial flow dominated by natural fracture effusion, fluid compensation of a matrix to the natural fracture, boundary effect and radial flow dominated by matrix effusion;
the evolution of the flow field of the homogeneous formation of the horizontal well comprises radial flow taking a shaft as a center, planar linear flow perpendicular to the horizontal well and planar pseudo-radial flow of a ring well.
Preferably, the flow normalization pressure analysis method performs flow normalization processing on the complex variable-yield and variable-pressure data, so as to integrate the production data into a pressure drop test curve under the condition of constant unit yield equivalent to the production data for production, and further perform log-log fitting on the measured curve to perform the reservoir model flow field analysis.
Preferably, the reforming pressure in the flow normalized pressure (RNP) analysis method is defined as, wherein:
oil well:
RNP flow normalized pressure, Mpa/(m3/d)
Delta P production differential pressure, MPa
q: daily output, m3/d
Pi: original formation pressure, MPa
Pwf: bottom hole pressure, MPa
Gas wells:
Δ m (p): pressure difference to be produced, MPa
Q: yield, m3/d
m(Pi): pseudo-original pressure, MPa
m(Pwf): pseudo bottom hole pressure, MPa
The flow normalized pressure or the flow normalized pseudo-pressure is subjected to the derivation of the material balance time
Preferably, a pressure recovery double-logarithm fitting curve graph, an RNP double-logarithm fitting curve graph and a corresponding relation chart between the flow field characteristics are constructed, and the flow field characteristics of the geological reservoir can be accurately identified by using the chart.
Preferably, the flow field characteristics corresponding to the pressure recovery curve and the RNP hyperbola include radial flow field characteristics, linear flow field characteristics, bilinear flow field characteristics, pseudo-steady flow field characteristics, and constant pressure boundary, which are respectively embodied as,
radial flow field characteristics: (1) present in an infinite formation, (2) derivative mid-term plateau;
linear flow field characteristics: (1) the infinite diversion vertical crack is caused, (2) the curve shows the slope of 1/2, (3) the pressure and derivative numerical value are 2 times different;
bilinear flow field characteristics: (1) limited diversion vertical fracture (2) curve shows a slope of 1/4, (3) the pressure is 4 times different from the derivative value;
simulating steady-state flow field characteristics: (1) the slope of the late curve is 1 (2) and the pressure is superposed with the late curve of the derivative;
constant pressure boundary characteristics: (1) the slope of the late stage of the curve is 0 (2) and the rapid speed regulation of the late stage of the derivative curve is (3) caused by the constant pressure boundary.
Preferably, the reservoir parameters including permeability and skin coefficient, fracture conductivity, drainage volume, pressure recovery pressure boundary and RNP pressure boundary can be obtained by calculating different flow pattern stages through flow pattern identification,
the permeability and the skin factor of the formation can be obtained through the radial flow phase,
the half length or permeability of the crack in the reservoir fracturing well can be obtained through linear flow,
the dual linear flow can be used to find fracture conductance,
the size of the bleed flow volume is estimated by solving for the pore volume within the bleed flow volume by a pseudo steady state flow,
k: permeability, md
μ: viscosity of the fluid, mPas
h: thickness of reservoir, m
Pd: dimensionless pressure
M: the pseudo pressure P.
Preferably, the reserve analysis and calculation is further performed by static pressure-net output volume, flow pressure-cumulative output and production dynamic methods based on the RNP analysis method.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
1. the method can analyze the condition that the yield and the pressure of the gas well change along with time at the normal production stage, and the production data can analyze the natural decreasing rule of the yield and the pressure by considering that the gas well is produced in a natural decreasing mode and does not have artificial supplementary energy;
2. the method can analyze the data only by adopting the output and pressure data measured every day, the data can be directly obtained, the longer the production time is, the larger the data size is, the limitation of the testing time is avoided, the well shut-in test is not needed, and the normal production of the gas well is not influenced;
3. the daily test productivity and the pressure data point density adopted by the method are small, the bottom flow pressure data of the oil-gas well can be obtained by converting the well head pressure, and the data processing and analysis are more convenient;
4. even if the yield and the pressure obtained by the production data are naturally changed, the method can obtain more accurate stratum parameters and yield calculation results under the condition of changing the yield and the pressure;
5. the method of the present invention generally describes reservoir characteristics throughout the well control range, as long as production time is long enough, and the well control boundaries are not detected by pressure recovery during most well shutdowns.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a schematic flow diagram illustrating a method for evaluating high pressure gas reservoir parameters based on long term production data from a hydrocarbon well, according to an exemplary embodiment;
FIG. 2 is a log-log fit of annual pressure recovery in an example;
FIG. 3 is a graph of RNP production history and pressure history and a Log-Log fit in the examples;
FIG. 4 is a graph of actual production and RNP theoretical log-log for a gas well in an example;
FIG. 5 is a schematic diagram of the evolution of the flow field of five basic formation models in the example;
FIG. 6 is a schematic diagram of pressure derivative changes of flow field evolution of a horizontal well homogeneous formation in an embodiment;
FIG. 7 is a flow field characteristic of the pressure recovery well testing log and the RNP well testing analysis log in the embodiment.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments of the invention to enable those skilled in the art to practice them. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. The scope of embodiments of the invention encompasses the full ambit of the claims, as well as all available equivalents of the claims. Embodiments may be referred to herein, individually or collectively, by the term "invention" merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed. The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the structures, products and the like disclosed by the embodiments, the description is relatively simple because the structures, the products and the like correspond to the parts disclosed by the embodiments, and the relevant parts can be just described by referring to the method part.
It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
The invention is further described with reference to the following figures and examples:
the method for measuring the pore compression coefficient of the large-scale fracture medium shown in FIG. 1 comprises the following steps:
s1: analyzing a compact sandstone reservoir model of a certain DK block to obtain a pressure derivative change rule of stratum flow field evolution as shown in FIG. 6;
s2: collecting production data by applying flow normalized pressure (RNP) analysis according to pressure derivative change rule data of the formation flow field evolution of S1, and integrating the production data into equivalent constant unit production pressure drop behavior data;
s3: according to the data analyzed in the S2, drawing a log-log curve by applying the RNP method, and identifying flow field characteristics similar to those in a pressure drop test as shown in FIG. 4;
s4: fitting a theoretical plate with the double logarithmic curve of S3 to identify the type of the formation flow field;
s5: and calculating different flow pattern stages to obtain reservoir parameters based on the stratum flow field type of S4.
Further, in step S5, the reservoir parameters obtained by calculating the different flow pattern stages specifically include permeability and skin coefficient, fracture conductivity, drainage volume, pressure recovery pressure boundary, and RNP pressure boundary.
According to the scheme, the reservoir model comprises a straight well homogeneous circular stratum, a straight well homogeneous rectangular stratum (a central well), a straight well homogeneous rectangular stratum (a single-sided well), a fractured straight well homogeneous stratum, a straight well natural fracture stratum and a horizontal well homogeneous stratum, and also comprises a combination form of the common oil and gas well and the reservoir model.
According to the scheme, further, the pressure derivative change analysis has different evolution forms for different reservoirs, and is specifically shown in fig. 5a to 5f in fig. 5.
The flow field evolution of the vertical homogeneous circular formation is shown in FIG. 5a, and comprises a shaft reservoir effect, a near-well radial flow analysis and a boundary effect analysis;
the vertical well homogeneous rectangular stratum (central well) flow field evolution diagram 5b comprises a shaft storage effect, a near well radial flow analysis, a boundary effect and a river course linear flow analysis;
the vertical well homogeneous rectangular formation (single-sided well) flow field evolution diagram is shown in fig. 5c, and comprises near-well radial flow analysis, single-sided effect response, boundary effect and river course linear flow analysis;
the homogeneous rectangular formation flow field evolution diagram of the fractured vertical well is shown in a figure 5d, and comprises linear flow in a crack, model flow of a vertical crack steamed dumpling in a linear flow stem reservoir in the crack, pseudo radial flow of a ring crack and linear flow of the reservoir perpendicular to the crack surface;
the vertical well natural fracture formation flow field evolution is shown in fig. 5e, and comprises natural fracture effusion dominated radial flow, fluid compensation of matrix to natural fracture, boundary effect and matrix effusion dominated radial flow;
the horizontal well homogeneous formation flow field evolution is shown in fig. 5f and comprises radial flow with a shaft as the center, planar linear flow perpendicular to the horizontal well and planar pseudo-radial flow around the horizontal well.
According to the scheme, further, the flow normalized pressure analysis method collects production data of 18 straight wells and 5 horizontal wells, and performs flow normalized processing on complex variable-yield and variable-pressure data, so that a pressure drop test curve under the condition that the production data of 23 wells are equivalent to the production data of constant unit yield is integrated, and further log fitting can be performed on an actually measured curve to perform flow field analysis on the reservoir model; according to the past shut-in pressure recovery test record, the pressure recovery test data of 6 times in the past 8 years of production are subjected to pressure recovery well test analysis, and a pressure recovery log curve is obtained and is shown in fig. 2.
Further according to the above aspect, the reforming pressure in the flow normalized pressure (RNP) analysis method is defined as,
oil well:
RNP flow normalized pressure, Mpa/(m3/d)
The delta P is the production pressure difference, MPa, the value is generally 0.2-7MPa, and is selected according to the oil well condition, and can be 0.2MPa, 1MPa, 5MPa, 7MPa and the like
q: daily output, m3The value of/d is generally 15-300, and is selected according to the oil well condition
Pi: original formation pressure, MPa
Pwf: bottom hole pressure, MPa
Gas wells:
Δ m (p): pressure difference to be produced, MPa
Q: yield, m3/d
m(Pi): pseudo-original pressure, MPa
m(Pwf): pseudo bottom hole pressure, MPa
The flow normalized pressure or the flow normalized pseudo-pressure is subjected to the derivation of the material balance time
According to the scheme, a pressure recovery double-logarithm fitting curve graph, an RNP double-logarithm fitting curve graph and a corresponding relation chart between the flow field characteristics are further constructed, and the chart can be used for accurately identifying the flow field characteristics of the geological reservoir.
According to the above scheme, further, the corresponding flow field characteristics of the pressure recovery curve and the RNP hyperbola include a radial flow field characteristic, a linear flow field characteristic, a bilinear flow field characteristic, a pseudo-steady-state flow field characteristic, and a constant pressure boundary, which are respectively embodied as shown in fig. 7,
radial flow field characteristics: (1) present in an infinite formation, (2) derivative mid-term plateau;
linear flow field characteristics: (1) the infinite diversion vertical crack is caused, (2) the curve shows the slope of 1/2, (3) the pressure and derivative numerical value are 2 times different;
bilinear flow field characteristics: (1) limited diversion vertical fracture (2) curve shows a slope of 1/4, (3) the pressure is 4 times different from the derivative value;
simulating steady-state flow field characteristics: (1) the slope of the late curve is 1 (2) and the pressure is superposed with the late curve of the derivative;
constant pressure boundary characteristics: (1) the slope of the later period of the curve is 0 (2) and the rapid speed regulation of the later period of the derivative curve is (3) caused by the constant pressure boundary;
after a log-log curve of the production data of the well in the past eight years is drawn, the flow field characteristics of the reservoir are identified according to a theoretical plate and a fitted measured curve, as shown in fig. 3.
According to the scheme, further, the reservoir parameters including permeability and skin coefficient, fracture conductivity, leakage flow volume, pressure recovery pressure boundary and RNP constant pressure boundary can be obtained by calculating different flow pattern stages through flow pattern recognition,
the permeability and the skin factor of the formation can be obtained through the radial flow phase,
the half length or permeability of the crack in the reservoir fracturing well can be obtained through linear flow,
the dual linear flow can be used to find fracture conductance,
the size of the bleed flow volume is estimated by solving for the pore volume within the bleed flow volume by a pseudo steady state flow,
k: permeability, md
μ: viscosity of the fluid, mPas
h: thickness of reservoir, m
Pd: dimensionless pressure
M: the pseudo pressure P.
"pseudo" pressure corresponds to "true". For example, in mathematical solution, there are a real space and a pseudo space (which can be understood as an assumed space) and the corresponding solutions are a real space solution and a pseudo space solution.
The following parameters were calculated using the above formula, as shown in table 1 below:
according to the scheme, the reserves can be further analyzed and calculated by methods such as static pressure-net output volume, flow pressure-cumulative output and production dynamic methods based on the RNP analysis method.
According to the scheme, the production data well testing analysis method is successfully applied to the field, particularly has good applicability to high-pressure gas reservoirs, unconventional oil and gas reservoirs with poor permeability and oil and gas wells which are not suitable for pressure recovery testing, and can accurately calculate formation parameters when pressure recovery testing data are lacked.
According to the scheme, further, the method not only can reliably explain the reservoir constant pressure boundary, but also can provide related results such as single well reserves and the like.
The reservoir parameters calculated by the RNP analysis method are more uniform with the formation parameters obtained by multiple pressure recovery test analysis, the formation does not have obvious change in the whole production process, when the production time of the oil and gas well is long enough, the RNP analysis method can also obtain the same result as the pressure recovery explanation, the formation properties reflected by the pressure recovery and the production data are the same, and the method is correct and effective in the evaluation method of the high-pressure gas reservoir parameters based on the long-term production data of the oil and gas well.
It is to be understood that the present invention is not limited to the procedures and structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (10)
1. A method for calculating reservoir parameters of a high pressure gas reservoir based on production data of a hydrocarbon well, comprising:
s1: analyzing the pressure derivative change of the flow field evolution of the reservoir model to obtain the pressure derivative change rule of the formation flow field evolution;
s2: collecting production data by applying flow normalized pressure (RNP) analysis according to pressure derivative change rule data of the formation flow field evolution of S1, and integrating the production data into equivalent constant unit production pressure drop behavior data;
s3: according to the data analyzed in the S2, drawing a double-logarithm curve by applying the RNP method, and identifying flow field characteristics similar to those in a pressure drop test;
s4: fitting a theoretical plate with the double logarithmic curve of S3 to identify the type of the formation flow field;
s5: and calculating different flow pattern stages to obtain reservoir parameters based on the stratum flow field type of S4.
2. The method of claim 1, wherein the reservoir parameters calculated for different flow pattern phases include permeability and skin factor, fracture conductivity, drainage volume, pressure recovery margin, and RNP margin.
3. The method for calculating the reservoir parameters of the high-pressure gas reservoir based on the oil-gas well production data as claimed in claim 1, wherein the reservoir model comprises a straight-well homogeneous circular stratum, a straight-well homogeneous rectangular stratum (central well), a straight-well homogeneous rectangular stratum (single-sided well), a fractured straight-well homogeneous stratum, a straight-well natural fracture stratum and a horizontal-well homogeneous stratum, and also comprises a combination form of the common oil-gas well and the reservoir model.
4. The method of calculating high pressure gas reservoir parameters based on oil and gas well production data as claimed in claim 1, wherein the pressure derivative variation analysis has different forms of evolution for different reservoirs,
the vertical well homogeneous circular formation flow field evolution comprises a shaft reservoir effect, near well radial flow analysis and boundary effect analysis;
the vertical well homogeneous rectangular stratum (central well) flow field evolution comprises a shaft reservoir effect, a near well radial flow analysis, a boundary effect and a river linear flow analysis;
the flow field evolution of the vertical homogeneous rectangular stratum (single-sided well) comprises near-well radial flow analysis, single-sided boundary effect response, boundary effect and river linear flow analysis;
the evolution of a flow field of a homogeneous rectangular stratum of a fracturing vertical well comprises linear flow in a crack, model flow of a vertical crack steamed dumpling in a linear flowing dry reservoir in the crack, pseudo radial flow of a ring crack and linear flow of the reservoir perpendicular to the crack surface;
the flow field evolution of the vertical well natural fracture stratum comprises radial flow dominated by natural fracture effusion, fluid compensation of a matrix to the natural fracture, boundary effect and radial flow dominated by matrix effusion;
the evolution of the flow field of the homogeneous formation of the horizontal well comprises radial flow taking a shaft as a center, planar linear flow perpendicular to the horizontal well and planar pseudo-radial flow of a ring well.
5. The method for calculating the parameters of the high-pressure gas reservoir based on the production data of the oil and gas well as recited in claim 1, wherein the flow normalization pressure analysis method is used for carrying out flow normalization processing on the complex variable-yield and variable-pressure data, so as to integrate the production data into a pressure drop test curve under the condition of producing the constant unit yield equivalent to the production data, and further carrying out log-log fitting on the measured curve to carry out the flow field analysis of the reservoir model.
6. The method of calculating high pressure gas reservoir parameters based on oil and gas well production data as claimed in claim 5, wherein the flow normalized pressure (RNP) analysis method wherein the reforming pressure is defined as, wherein:
oil well:
RNP flow normalized pressure, Mpa/(m3/d)
Delta P production differential pressure, MPa
q: daily output, m3/d
Pi: original formation pressure, MPa
Pwf: bottom hole pressure, MPa
Gas wells:
Δ m (p): pressure difference to be produced, MPa
Q: yield, m3/d
m(Pi): pseudo-original pressure, MPa
m(Pwf): pseudo bottom hole pressure, MPa
The flow normalized pressure or the flow normalized pseudo-pressure is subjected to the derivation of the material balance time
7. The method of claim 1, wherein a pressure recovery log-log fit graph, an RNP log-log fit graph and a chart of correspondence between the flow field characteristics are constructed, and the chart is used to accurately identify the flow field characteristics of the geological reservoir.
8. The method of claim 7, wherein the pressure recovery curve and RNP hyperbola corresponding flow field characteristics include radial flow field characteristics, linear flow field characteristics, bilinear flow field characteristics, pseudo-steady flow field characteristics and constant pressure boundary, each of which is embodied as,
radial flow field characteristics: (1) present in an infinite formation, (2) derivative mid-term plateau;
linear flow field characteristics: (1) the infinite diversion vertical crack is caused, (2) the curve shows the slope of 1/2, (3) the pressure and derivative numerical value are 2 times different;
bilinear flow field characteristics: (1) limited diversion vertical fracture (2) curve shows a slope of 1/4, (3) the pressure is 4 times different from the derivative value;
simulating steady-state flow field characteristics: (1) the slope of the late curve is 1 (2) and the pressure is superposed with the late curve of the derivative;
constant pressure boundary characteristics: (1) the slope of the late stage of the curve is 0 (2) and the rapid speed regulation of the late stage of the derivative curve is (3) caused by the constant pressure boundary.
9. The method of claim 1, wherein the pattern recognition is performed to calculate reservoir parameters including permeability and skin coefficient, fracture conductivity, drainage volume, pressure recovery pressure boundary, and RNP pressure boundary for different pattern stages,
the permeability and the skin factor of the formation can be obtained through the radial flow phase,
the half length or permeability of the crack in the reservoir fracturing well can be obtained through linear flow,
the dual linear flow can be used to find fracture conductance,
the size of the bleed flow volume is estimated by solving for the pore volume within the bleed flow volume by a pseudo steady state flow,
k: permeability, md
μ: viscosity of the fluid, mPas
h: thickness of reservoir, m
Pd: dimensionless pressure
M: pseudo pressure, P.
10. The method of claim 1, wherein the RNP-based analysis further employs static pressure-net production volume, flow pressure-cumulative production and dynamic production methods for reserve analysis and calculation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010644070.6A CN113919240A (en) | 2020-07-07 | 2020-07-07 | High-pressure gas reservoir parameter calculation method based on oil and gas well production data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010644070.6A CN113919240A (en) | 2020-07-07 | 2020-07-07 | High-pressure gas reservoir parameter calculation method based on oil and gas well production data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113919240A true CN113919240A (en) | 2022-01-11 |
Family
ID=79231343
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010644070.6A Pending CN113919240A (en) | 2020-07-07 | 2020-07-07 | High-pressure gas reservoir parameter calculation method based on oil and gas well production data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113919240A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114166698A (en) * | 2022-02-08 | 2022-03-11 | 中国矿业大学(北京) | Method and system for evaluating gas diffusion capacity of coal micro-channel under competitive adsorption |
| CN115012925A (en) * | 2022-08-08 | 2022-09-06 | 西南石油大学 | Experimental determination method for vertical gas well shaft flow pattern under high pressure condition |
| CN115238600A (en) * | 2022-06-22 | 2022-10-25 | 中国石油大学(北京) | Oil-gas exploration method and device for calculating pressure derivative based on three-stage noise reduction |
| CN115796070A (en) * | 2022-11-04 | 2023-03-14 | 北京科技大学 | Method and device for identifying flow state change characteristics of reservoir of compact oil and gas reservoir |
| CN115828787A (en) * | 2022-12-13 | 2023-03-21 | 西南石油大学 | Improved MDH well testing analysis method |
| CN116579263A (en) * | 2023-05-17 | 2023-08-11 | 中国石油大学(北京) | Comprehensive analysis method based on oil and gas well drainage dynamic data |
-
2020
- 2020-07-07 CN CN202010644070.6A patent/CN113919240A/en active Pending
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114166698A (en) * | 2022-02-08 | 2022-03-11 | 中国矿业大学(北京) | Method and system for evaluating gas diffusion capacity of coal micro-channel under competitive adsorption |
| CN115238600A (en) * | 2022-06-22 | 2022-10-25 | 中国石油大学(北京) | Oil-gas exploration method and device for calculating pressure derivative based on three-stage noise reduction |
| CN115238600B (en) * | 2022-06-22 | 2023-07-28 | 中国石油大学(北京) | Oil-gas exploration method and device based on three-section noise reduction calculation pressure derivative |
| CN115012925A (en) * | 2022-08-08 | 2022-09-06 | 西南石油大学 | Experimental determination method for vertical gas well shaft flow pattern under high pressure condition |
| US11773714B1 (en) | 2022-08-08 | 2023-10-03 | Southwest Petroleum University | Experimental method for determining flow patterns in vertical wellbore of gas wells at high-pressure conditions |
| CN115796070A (en) * | 2022-11-04 | 2023-03-14 | 北京科技大学 | Method and device for identifying flow state change characteristics of reservoir of compact oil and gas reservoir |
| CN115796070B (en) * | 2022-11-04 | 2023-12-01 | 北京科技大学 | Method and device for recognizing fluid change characteristics of tight oil and gas reservoir |
| CN115828787A (en) * | 2022-12-13 | 2023-03-21 | 西南石油大学 | Improved MDH well testing analysis method |
| CN115828787B (en) * | 2022-12-13 | 2023-09-08 | 西南石油大学 | Improved MDH well test analysis method |
| CN116579263A (en) * | 2023-05-17 | 2023-08-11 | 中国石油大学(北京) | Comprehensive analysis method based on oil and gas well drainage dynamic data |
| CN116579263B (en) * | 2023-05-17 | 2024-01-30 | 中国石油大学(北京) | Comprehensive analysis method based on oil and gas well drainage dynamic data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113919240A (en) | High-pressure gas reservoir parameter calculation method based on oil and gas well production data | |
| CN111353205B (en) | Method for calculating formation pressure and dynamic productivity of water-producing gas well of tight gas reservoir | |
| CN104899411B (en) | A kind of reservoir productivity prediction model method for building up and system | |
| CN110656915B (en) | Shale gas multi-section fracturing horizontal well multi-working-system productivity prediction method | |
| CN106932324A (en) | A kind of method for determining High water cut sandstone oil reservoir reservoir permeability Changing Pattern | |
| Jamali et al. | Application of capacitance resistance models to determining interwell connectivity of large-scale mature oil fields | |
| CN105334293A (en) | Flow state identification method and device of tight gas in multi mediums | |
| CN114370269B (en) | Comprehensive determination method for physical property lower limit of effective reservoir of deep carbonate reservoir | |
| CN105678082B (en) | Double-pressure drop method for identifying type of oil-gas well acid fracturing communication reservoir | |
| CN112257349B (en) | Method for judging whether tight sandstone movable water-gas reservoir gas well has development value | |
| CN111287741B (en) | Rapid calculation method for permeability of compact oil reservoir volume fracturing transformation area | |
| CN114577677B (en) | Compact oil reservoir nonlinear seepage characterization method based on reservoir heterogeneity | |
| CN113065246B (en) | Stratum parameter inversion method based on perforation test combined system | |
| CN111734383B (en) | Fracturing test and interpretation method for obtaining stratum closing pressure | |
| CN115705452A (en) | Novel recovery ratio prediction method for middle and later stages of integrated sandstone reservoir development | |
| CN114066666A (en) | Method for analyzing connectivity among wells through injection-production profile monitoring data | |
| CN111594113B (en) | Dynamic inversion method for opening of cracks between tight reservoir wells | |
| CN113719271B (en) | Well test design parameter correction method | |
| CN109958429B (en) | Method for judging shale gas adsorption gas output | |
| CN111764882B (en) | Fracturing design optimization method for optimizing proppant concentration by adopting chemical agent | |
| CN117077419B (en) | Novel formation pressure analysis method for fracture-cavity oil reservoir | |
| CN110388202A (en) | Wellbore fluids Rheology Method based on the reading prediction of high temperature and pressure viscosimeter | |
| CN116124667B (en) | Shale gas reservoir permeability characterization method | |
| CN111651848B (en) | Stress-sensitive oil reservoir vertical well fluid production capacity prediction method and device | |
| CN110705026A (en) | Method for quantitatively evaluating steam thermal front equilibrium of thermal recovery reservoir based on kini coefficient |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |