CN113719271A - Well test design parameter correction method - Google Patents

Well test design parameter correction method Download PDF

Info

Publication number
CN113719271A
CN113719271A CN202111291366.5A CN202111291366A CN113719271A CN 113719271 A CN113719271 A CN 113719271A CN 202111291366 A CN202111291366 A CN 202111291366A CN 113719271 A CN113719271 A CN 113719271A
Authority
CN
China
Prior art keywords
well
test
pressure
permeability
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.)
Granted
Application number
CN202111291366.5A
Other languages
Chinese (zh)
Other versions
CN113719271B (en
Inventor
赵洪绪
房鑫磊
于伟强
赵洪涛
杨毅
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China France Bohai Geoservices Co Ltd
Original Assignee
China France Bohai Geoservices Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by China France Bohai Geoservices Co Ltd filed Critical China France Bohai Geoservices Co Ltd
Priority to CN202111291366.5A priority Critical patent/CN113719271B/en
Publication of CN113719271A publication Critical patent/CN113719271A/en
Application granted granted Critical
Publication of CN113719271B publication Critical patent/CN113719271B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E21B47/06—Measuring temperature or pressure
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E21B47/06—Measuring temperature or pressure
    • E21B47/07—Temperature
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
    • E21B49/08—Obtaining fluid samples or testing fluids, in boreholes or wells
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
    • E21B49/08—Obtaining fluid samples or testing fluids, in boreholes or wells
    • E21B49/087—Well testing, e.g. testing for reservoir productivity or formation parameters
    • E21B49/0875—Well testing, e.g. testing for reservoir productivity or formation parameters determining specific fluid parameters
    • 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
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Mining

Abstract

The invention discloses a well testing design parameter correction method, which relates to the technical field of well testing parameter design and comprises the following steps: the method comprises the following steps: selecting well test design parameters according to data such as well wall coring, well logging, well-approaching test and the like, and carrying out preliminary well test design; step two: obtaining the yield Q and the bottom hole flowing pressure p after the flowing pressure gradient test is finishedwfAccording to Q-pwfUpdating the permeability or the skin coefficient of the initial well test design according to the corresponding relation; step three: using updated trialsThe well design guides the productivity test and the pressure recovery test process, so that the productivity test working system and the pressure recovery well shut-in time are more reasonable. Under the condition of difficult parameter optimization, the invention can overcome the uncertainty in the selection process of the well test design parameters, improve the test success rate and save the operation cost.

Description

Well test design parameter correction method
Technical Field
The invention relates to the technical field of well test parameter design, in particular to a well test design parameter correction method.
Background
The proportion of low-permeability oil reservoir reserves in China is large, but low-permeability oil fields are poor in geological conditions and high in development difficulty, the demand on petroleum products is greater and greater along with the rapid development of economy in China, and the rich petroleum reserves of the low-permeability oil fields are more and more concerned. Due to the existence of low-permeability reservoir fractures and the directionality of the deposition process, the formation permeability anisotropy with developed fractures is prominent, and obvious radial anisotropy is often shown in the reservoir development process.
The well test design parameters have larger uncertainty in the selection process, particularly for a reservoir with high low permeability and non-uniform property, the design parameters may have larger difference from the actual physical properties of the reservoir, so that the test working system and the pressure recovery shut-in time given by the well test design are unreasonable, and the test data is not credible or even the test fails.
Disclosure of Invention
The invention aims to solve the problems that a test working system and pressure recovery shut-in time given by a test design are unreasonable due to large uncertainty of the test design parameters in the selection process in the prior art, so that test data is not credible and even the test fails.
In order to achieve the purpose, the invention adopts the following technical scheme:
a well test design parameter correcting method comprises the following steps: the method comprises the following steps: selecting well test design parameters according to data such as well wall coring, well logging, well-approaching test and the like, and carrying out preliminary well test design;
step two: obtaining the yield Q and the bottom hole flowing pressure p after the flowing pressure gradient test is finishedwfAccording to Q-pwfThe corresponding relation is updated, and the permeability or the table of the preliminary well testing design is updatedSkin factor;
step three: and the updated well testing design is used for guiding the productivity testing and pressure recovery testing processes, so that the productivity testing working system and the pressure recovery well shut-in time are more reasonable.
Preferably, in the first step, the selection of the well testing design parameters is performed according to the data of the side-wall coring, the well logging, the well-approaching test and the like, and the method for performing the preliminary well testing design comprises the following steps:
s1 fluid high pressure physical property Parameter (PVT): for wells with downhole fluid PVT reports, it is very accurate to directly use the results made by the laboratory in the PVT report; the method for selecting the test wells has the advantages that sampling analysis is not carried out at the early stage of the test wells, and high-pressure physical property parameters of adjacent wells at the same layer are referred, so that the selection method is very close to the actual selection method although a certain deviation exists, and can be ignored and not recorded; for a first pre-exploration well or a development well of a tested reservoir, the result can be explained by referring to MDT (cable formation testing) in the well-digging process, and if the MDT (cable formation testing) item is not added in the well-digging process, the high-pressure physical property parameters of the fluid at the same layer of other areas can only be referred.
S2 effective permeability: the method for selecting the initial design permeability comprises the steps of carrying out correlation analysis on the existing well logging permeability and the effective permeability of a test well, substituting the well logging permeability in the early-stage data into a curve relation according to a distribution diagram and a corresponding relation curve of the regression testing and the test well permeability to obtain the effective permeability of the initial well testing design; because of the influence of the number of wells participating in regression at the early stage and the correlation coefficient of regression, the difference between the design value and the true value of the effective permeability is large, and then the parameter has great influence on the accuracy of the well test design in the well test design, the significance of the invention lies in that the permeability is corrected through other modes, and the primary design is improved.
Because the test well can not obtain accurate stratum effective permeability data before operation, the correlation between the logging permeability and the testing effective permeability needs to be searched on the basis of the existing test data, the physical property parameters of different reservoirs are analyzed, the reservoirs are comprehensively classified, the permeability data are counted, and a permeability distribution map can be drawn.
S3 reservoir effective thickness: selecting effective thickness by using a logging interpretation result, selecting effective oil and gas layers, and removing the thickness of a dry layer; in the actual parameter selection, the effective thickness of the effective reservoir communicated with the shaft in the well logging interpretation result is finally selected by combining the completion mode, namely the perforation well or the open hole well.
The effective thickness of the reservoir is selected according to seismic profile, construction diagram and logging data as reference during well test design. The effective thickness of the reservoir is selected, and the well testing design result is mainly influenced by the reservoir stratum coefficient kh.
S4, in the aspect of skin coefficient consideration, the influence of the drilling fluid on a reservoir stratum during drilling operation, the operation of whether the test well is acidized and fractured or not, the type of an oil and gas reservoir and the type of a well are taken into consideration, and when the drilling fluid soaks the reservoir stratum for a long time due to the conditions of abnormal weather, tool problems and the like existing in the drilling process, the positive skin is given according to the soaking time and a reservoir stratum pollution degree chart; giving a negative skin for the measure well according to the evaluation and analysis result after the measure; for wells of complex well types and high-production gas wells, reference is made to similar historical wells; for test wells without special cases, the skin factor is given 0.
The skin factor reflects the additional pressure drop caused by bottom hole pollution and other factors, and the well test design parameters need to be judged according to the actual pollution situation during the well drilling and completion, such as: loss in the drilling process, soaking time of drilling fluid on a reservoir stratum, a well completion mode, sand prevention and the like, and for a directional well or a horizontal well, the geometric skin caused by the inclination of a shaft needs to be considered; it is also desirable for high producing gas wells to take into account the apparent skin effects caused by the gas's non-Darcy flow downhole.
S5, solving a mathematical model: for the condition of comparative development of microcracks in a buried-hill low-permeability reservoir, a reservoir characteristic curve shows the characteristics of a dual-pore medium model, and the dual-pore medium well testing mathematical model is solved in a Laplace space:
Figure 982912DEST_PATH_IMAGE001
(1)
in the formula:
Figure 701469DEST_PATH_IMAGE002
a Laplace space solution of bottom hole pressure; u is a Laplace space independent variable; f (u) is a function with respect to the argument u; k0(x)、K1(x) Respectively, zero order and first order imaginary vector Bessel functions; cDDimensionless well reservoir coefficients; s is the epidermis coefficient.
And for the transition section in the flowing period of the dual-pore medium, performing inversion of a Laplace space solution, and obtaining by derivation of the solution pressure:
Figure 890005DEST_PATH_IMAGE003
(2)
wherein:
Figure 668605DEST_PATH_IMAGE004
；
Figure 208171DEST_PATH_IMAGE005
in the formula: t is tDDimensionless time; cDDimensionless well reservoir coefficients; h is the reservoir thickness; r iswIs the wellbore radius; ctIs the comprehensive compression coefficient; c is a wellbore storage coefficient; kfPermeability of the fracture system; phi is porosity; omega is the energy storage ratio; λ is the cross-flow coefficient.
Parameters in the mathematical model mainly relate to omega as an energy storage ratio and lambda as a channeling coefficient, the two parameters mainly come from given values of oil reservoir combined logging and logging information, and if no adjacent well information parameters can be referred, the selection method is closer and has little difference.
As can be seen from the pressure derivative formula of the double-hole model, the permeability, the reservoir capacity of the matrix system and the cross-flow coefficient have large influences on the radial flow position and the cross-flow transition section form, and design parameters need to be optimized in order to accurately guide the pressure recovery test and the productivity test of a well test by utilizing well test design data.
Preferably, the yield Q and the bottom hole flowing pressure p are obtained in the second stepwfAccording to Q-pwfCorrespondence update testA method of permeability or skin factor for a well design comprising the steps of:
a1, placing a pressure gauge in the middle of the gas layer, and stably producing according to a designed working system;
a2, testing the flow pressure gradient;
a3, after the flow pressure gradient test is finished, the pressure gauge is lifted out of the wellhead to read data;
a4 obtaining production Q and bottom hole flow pressure pwfAccording to Q-pwfThe corresponding relation is as follows:
Figure 527157DEST_PATH_IMAGE006
in the formula: piIs the original formation pressure; pwfBottom hole flow pressure; q. q.sgThe well head yield; k is the effective permeability of the formation; h is the effective thickness of the stratum;
Figure 835778DEST_PATH_IMAGE007
is the reservoir condition viscosity;
Figure 519700DEST_PATH_IMAGE008
、
Figure 77721DEST_PATH_IMAGE009
respectively, gas deviation coefficient and average temperature under formation conditions; psc、TscRespectively, pressure and temperature under a gas standard state; phi is porosity; ctIs the comprehensive compression coefficient; t is time; r iswIs the radius of the well; saTo look at the skin coefficient, Sa=S+DqgS is the epidermis coefficient and D is the non-Darcy flow coefficient.
After the preliminary well test design is completed, all parameters in the formula are known quantities; after the flowing pressure gradient is obtained to be tested, substituting the measured output and the bottom flowing pressure into the mathematical model to obtain the permeability k after the well test design is updated, embedding the mathematical model into commercial software in actual operation, and only adjusting the permeability k to enable the flowing pressure value generated by simulation to be equal to the measured flowing pressure value without manual calculation; the relationship between the two is existing, and can be inquired in books of 'gas reservoir dynamic description and well testing' of the Zhuang-Hui-nong teacher.
And adjusting the permeability or the skin coefficient of the preliminary well testing design to ensure that the simulated pressure value is matched with the actually measured pressure value.
Compared with the prior art, the invention has the following advantages:
1. the invention utilizes the bottom hole flowing pressure test data to correct and update the well test design parameters in real time, and guides the productivity test and pressure recovery test process, so that the productivity test working system and the pressure recovery shut-in time are more reasonable;
2. under the condition of difficult parameter optimization, the invention can overcome the uncertainty in the selection process of the well test design parameters, improve the test success rate and save the operation cost.
In conclusion, under the condition that the parameters are difficult to optimize, the method can overcome the uncertainty in the well test design parameter selection process, improve the test success rate and save the operation cost.
Drawings
FIG. 1 is a table of main design parameters of a well test design parameter correction method according to the present invention;
FIG. 2 is a double logarithmic graph of the preliminary well test design for the case of comparative development of microcracks in a low permeability reservoir in a buried hill and with a pressure derivative curve having a concave characteristic, wherein the upper curve in the graph represents a differential pressure curve and the lower curve represents a pressure derivative curve;
FIG. 3 is a data reading diagram of a pressure gauge lifting a wellhead after the completion of the flow pressure gradient test of the present invention;
FIG. 4 is a graph showing the matching between simulated pressure values and actual measured pressure values obtained by adjusting the permeability or skin coefficient of the well test design;
FIG. 5 is a graph of log-log curve comparison analysis of preliminary well test design, updated well test design and actual measured data in accordance with the present invention;
FIG. 6 is a comparison table of well testing interpretation results and design parameters according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1-6, a well testing design parameter correction method includes the following steps:
the method comprises the following steps: according to the seepage theory, the main factors influencing the test productivity and the test curve form comprise fluid high-pressure physical property parameters, effective permeability, bottom hole pollution conditions, structures and boundaries, and for a buried hill reservoir with micro-crack development, the main factors also comprise the energy storage ratio, the channeling coefficient and the like of a dual-pore medium model, and the test design parameters are selected according to the data of well wall coring, well logging, well-approaching test and the like to carry out initial test design;
step two: for an earlier developed well, if a downhole permanent pressure gauge is not provided, the productivity test is not carried out, and the conditions of the average formation pressure and the production index at the bottom of the well cannot be mastered. In addition to directly reading the pressure gauge data, the storage type pressure gauge can be used for performing a flow pressure test of a working system before the pressure recovery test, and after the flow pressure data is obtained, the yield Q and the bottom hole flow pressure p are obtainedwfAccording to Q-pwfUpdating the permeability or the skin coefficient of the initial well test design according to the corresponding relation;
step three: and the updated well testing design is used for guiding the productivity testing and pressure recovery testing processes, so that the productivity testing working system and the pressure recovery well shut-in time are more reasonable.
In the first step, the selection of well testing design parameters is carried out according to data such as side-wall coring, well logging, well-approaching test and the like, and the method for carrying out preliminary well testing design comprises the following steps:
s1 fluid high pressure physical property Parameter (PVT): the high-pressure physical property of the fluid is a basic parameter in well test design and well test explanation, and if the difference between the design parameter and the physical property of the reservoir fluid is large, particularly the viscosity, the volume coefficient, the compression coefficient and the like, the yield prediction and well test design result may have large deviation from the actual situation.
For a well with a downhole fluid PVT report, directly using results made by a laboratory in the downhole fluid PVT report, wherein the specific results comprise formation pressure, temperature, density, viscosity, volume coefficient, compressibility, dew point pressure, bubble point pressure, formation water mineralization degree, deviation factors and fluid component analysis of the downhole fluid under formation conditions;
for wells which are not subjected to sampling analysis at the early stage of the test well, using high-pressure physical property parameters in a PVT report of the downhole fluid adjacent to the well at the same layer;
for a first pre-exploration well or a development well of a tested reservoir, MDT (cable formation testing) in the well drilling process is used for explaining pressure, temperature and flow values in results, other parameters use high-pressure physical property parameter values in PVT reports of other blocks of the same-layer well with underground fluid sampling, and for the first pre-exploration well or the development well of the tested reservoir, if construction projects in the well drilling process are few and the well does not have high-pressure physical property parameters which can be directly used, the high-pressure physical property parameters of the fluids of the same-layer wells of other blocks are directly used, so that the parameter error is relatively large.
The fluid high pressure physical Property (PVT) parameters must include one, two, or more of formation condition pressure, temperature, density, viscosity, volume coefficient, compressibility, dew point pressure, bubble point pressure, formation water mineralization, deviation factor, fluid composition analysis data.
S2 effective permeability: because the test well can not obtain accurate stratum effective permeability data before operation, the correlation between the logging permeability and the testing (effective) effective permeability needs to be searched on the basis of the existing test data, the physical property parameters of different reservoirs are analyzed, the reservoirs are comprehensively classified, the permeability data are counted, and a permeability distribution map can be drawn; however, different sedimentary basins, different types of oil and gas fields and different oil reservoirs have different distribution characteristics of logging permeability and well testing dynamic permeability, and are limited by the number of statistical samples, and the design and the productivity prediction of well exploration and well development at the early stage have certain difficulty; for a low-permeability reservoir, the effective permeability is small in magnitude, if selection has errors, the vertical deviation condition of a well test design curve form is obvious, and effective guidance on the well shut-in time of testing and misjudgment on the detection range and the boundary condition of the reservoir are influenced.
The method for selecting the initial design permeability comprises the steps of carrying out correlation analysis on the permeability of a well to be tested and the permeability of a well to be tested in a known well to be tested in a block, firstly classifying the permeability of the well to be tested and the permeability of the well to be tested according to a development horizon according to a sedimentary facies, depicting all the permeability of the well to be tested as an abscissa and the permeability of the well to be tested (effective) as an ordinate under the same sedimentary facies, carrying out linear regression and polynomial regression, finding a regression relational expression with better correlation in the linear regression and polynomial regression, and finding the correlation process of the permeability of the well to be tested and the permeability of the well to be tested under each sedimentary facies. Finally, substituting the logging permeability into the relational expression according to the sedimentary facies where the testing horizon of the testing well is located and the regression corresponding relational expression of the logging permeability, so as to obtain the (effective) permeability of the testing well of the primary testing design; for the well with poor correlation of the permeability of the well to be tested and tested, the permeability of the well to be tested is directly used as the effective permeability.
S3 reservoir effective thickness: the effective thickness of the reservoir is selected according to seismic profile, construction diagram and logging data as reference during well test design. Selecting the effective thickness of the reservoir, wherein the well testing design result is mainly influenced by the reservoir stratum coefficient kh; for reservoirs with serious heterogeneity, the heterogeneity of effective thickness should be fully considered, and equivalent thickness is established to replace the thickness heterogeneous reservoir, so as to effectively reduce design result errors. When the effective thickness of the oil deposit is not given according to the early-stage comprehensive data information, the effective thickness is selected by using a logging interpretation result, the effective thickness is selected by using the logging interpretation result, the sum of the effective thicknesses of the oil layer and the gas layer is selected,
the effective thickness sum excludes the dry layer thickness in the test section; the reservoir is effective during well testing design, and if the production logging interpretation result is optimal, the true value of the effective thickness of the reservoir can be directly obtained.
S4, the skin coefficient reflects the additional pressure drop caused by bottom hole pollution and other factors, and the well test design parameters need to be judged according to the actual pollution situation during the drilling and completion, such as: loss in the drilling process, soaking time of drilling fluid on a reservoir stratum, a well completion mode, sand prevention and the like, and for a directional well or a horizontal well, the geometric skin caused by the inclination of a shaft needs to be considered; the apparent skin effect caused by the non-Darcy flow of the gas at the bottom of the well needs to be considered for the high-yield gas well; when the drilling fluid is soaked in a reservoir for a long time under the abnormal operation condition, the positive epidermis is given according to the soaking time and the reservoir pollution degree chart, for a normal operation well, the soaking time of the drilling fluid in the reservoir is short, the reservoir pressure is in a balanced or under-balanced state, the pollution of the drilling fluid to the reservoir is ignored and not recorded, the soaking time of the drilling fluid can be inquired from an engineering operation record, and the soaking time and the reservoir pollution degree chart are measured by a laboratory; for the measure well, the negative epidermis is given according to the evaluation and analysis result after the measure, the evaluation and analysis result after the measure is the simulation value of related professional software, and only related professional result data are used; for a normal test well, the skin factor is given 0.
S5, solving a mathematical model: for the condition that the microcracks in the buried hill low permeability reservoir develop obviously, the reservoir characteristic curve can show the characteristics of a dual pore medium model, and the dual pore medium well testing mathematical model is solved in a Laplace space:
Figure 403660DEST_PATH_IMAGE001
(1)
in the formula:
Figure 301209DEST_PATH_IMAGE002
a Laplace space solution of bottom hole pressure; u is a Laplace space independent variable; f (u) is a function with respect to the argument u; k0(x)、K1(x) Respectively, zero order and first order imaginary vector Bessel functions; cDDimensionless well reservoir coefficients; s is the epidermis coefficient;
and for the transition section in the flowing period of the dual-pore medium, performing inversion of a Laplace space solution, and obtaining by derivation of the solution pressure:
Figure 218349DEST_PATH_IMAGE003
(2)
wherein:
Figure 732507DEST_PATH_IMAGE004
；
Figure 330979DEST_PATH_IMAGE005
in the formula: t is tDDimensionless time; cDDimensionless well reservoir coefficients; c is a wellbore storage coefficient; h is the reservoir thickness; r iswIs the wellbore radius; ctIs the comprehensive compression coefficient; kfPermeability of the fracture system; phi is porosity; omega is the energy storage ratio; λ is the cross-flow coefficient.
As can be seen from the pressure derivative formula of the double-hole model, the influence of the permeability, the reservoir capacity of a matrix system and the cross-flow coefficient on the radial flow position and the cross-flow transition section form is large. The two parameters of omega and lambda mainly come from given values of oil reservoir combined logging and logging information, the same-layer near-well logging interpretation result is used under the condition of data loss, and the design parameters need to be optimized in order to accurately guide the pressure recovery test and the productivity test of the logging by using the logging design data.
Obtaining the yield Q and the bottom hole flow pressure p in the second stepwfAccording to Q-pwfThe method for updating the permeability or the skin coefficient of the well test design according to the corresponding relation comprises the following steps, and the flow when the conventional test is carried out by utilizing the storage pressure gauge generally comprises the following steps:
a1, using a steel wire to carry a storage pressure gauge to be put down to the middle depth of the gas layer, stably producing according to a designed working system, and recording oil, casing pressure, yield measurement and water content testing during the testing period;
a2, lifting the pressure gauge and stopping at different depths to perform flowing pressure gradient test, reasonably selecting gradient point test intervals according to the structure, the well type and the well inclination of the pipe column, and reducing the influence of factors such as pressure fluctuation and artificial point taking on gradient value calculation;
a3, lowering a pressure gauge to the middle depth of the oil layer, and performing a shut-in pressure recovery test after the pressure gauge is stable;
a4, lifting the pressure gauge and stopping at different depths after the designed shut-in time is reached, and carrying out static pressure gradient test;
a5 lifting the pressure gauge up to the well head, playing back the data, and interpreting the pressure recovery.
In order to correct well testing design parameters and improve the accuracy and reliability of the pressure recovery testing shut-in time, the improved testing process comprises the following steps:
a1, placing a pressure gauge in the middle of the gas layer, stably producing according to the designed working system, and recording oil, casing pressure, yield measurement and water content test during the test;
a2, performing flowing pressure gradient test, reasonably selecting gradient point test intervals according to the structure of a pipe column, the well type and the well inclination, and reducing the influence of factors such as pressure fluctuation and artificial point taking on gradient value calculation;
a3, after the flow pressure gradient test is finished, the pressure gauge is lifted out of the wellhead to read data;
a4 obtaining production Q and bottom hole flow pressure pwfAccording to Q-pwfThe corresponding relation is that the number of the first and the second groups,
Figure 348613DEST_PATH_IMAGE006
in the formula: piIs the original formation pressure; pwfBottom hole flow pressure; q. q.sgThe well head yield; k is the effective permeability of the formation; h is the effective thickness of the stratum;
Figure 702234DEST_PATH_IMAGE007
is the reservoir condition viscosity;
Figure 172530DEST_PATH_IMAGE008
、
Figure 840271DEST_PATH_IMAGE009
respectively, gas deviation coefficient and average temperature under formation conditions; psc、TscRespectively, pressure and temperature under a gas standard state; phi is porosity; ctIs the comprehensive compression coefficient; t is time; r iswIs the radius of the well; saTo look at the skin coefficient, Sa=S+DqgS is the epidermis coefficient, D is the non-Darcy flow coefficient;
adjusting the permeability or the skin coefficient of the preliminary well testing design to enable the simulated pressure value to be matched with the actually measured pressure value;
a5, pressure recovery testing, capacity adjustment is carried out by using the updated well testing design, and well closing time is guided according to testing requirements;
a6, performing static pressure gradient test, wherein phase state and liquid level change in a shaft are analyzed in an auxiliary manner through comparison of flow and static pressure gradients, guidance is provided for final explanation, and pressure conversion can be assisted for wells with pressure gauges which cannot fall to the middle part of a reservoir due to the influences of well conditions, well types and other factors;
a7 pressure gauge lifts the well head and plays back the data, pressure recovery interpretation.
Yet another embodiment
Combining the test data of a W1 well of a certain gas field, adopting a well testing design parameter correction method based on flow pressure gradient, and comprising the following steps:
the method comprises the following steps: preliminary well test design
S1: fluid high-pressure physical property parameters: selecting the high-pressure physical Parameters (PVT) of the W1 well fluid, referring to a W2 well adjacent to the same layer, wherein the formation pressure is 48.72MPa, the formation temperature is 171.9 ℃, the volume coefficient is 0.0038, the viscosity is 0.0567mp.s, and the compression coefficient is 0.0076MPa-1。
S2: effective permeability: the effective permeability of the W1 well is referenced to the adjacent W2 well and is taken at 0.34 md.
S3: effective thickness of reservoir: the effective thickness of the well is explained to be 175.7m by logging;
s4: skin factor: the W1 well was gravel packed with open hole, no contamination measure was applied, and the skin factor was taken to be 0.
S5: solving a data model: and under the condition of gas production of 6 ten thousand square/day, solving according to the mathematical model to obtain the change condition of the bottom hole pressure along with the time. And (4) calculating the derivative of the pressure data, and displaying that the pressure data can meet the test requirement when the well is closed for 10 hours.
Step two
A1: the flow pressure gradient was tested by running in a storage manometer.
A2: and in the stage of flow pressure test, the production system of 6 ten thousand square/day is stably tested.
A3: and lifting the pressure gauge to the wellhead to read data.
A4: well capable of obtaining yield corresponding to 6 ten thousand squares/dayThe underflow pressure was 20.5 MPa. According to Q-pwfAnd updating the preliminary well testing design according to the corresponding relation so that the simulation pressure value is matched with the actual measurement pressure value.
A5: and obtaining the updated model permeability of 0.023md by utilizing the matching relation so as to regenerate the pressure data and the pressure derivative data according to the model. The radial flow occurrence time obtained at this time is 190 hours, and the minimum 250 hours of shut-in time meets the test requirement.
A6: and (4) shutting the well according to 290 hours in the pressure recovery test according to the calculation requirement, finishing the pressure recovery test to test the static pressure gradient, and then lifting the tool to download data.
A7: and (5) well testing and interpretation of the pressure recovery data, and obtaining the permeability of 0.025 md.
In conclusion, the invention effectively improves the design quality of the well test, more reasonably and effectively guides the pressure recovery test process, and the measured data of the bottom flowing pressure is matched with the simulation data to update the design parameters of the well test in real time and guide the productivity test and the pressure recovery test process, so that the working system of the productivity test and the time for shutting down the well for pressure recovery are more reasonable. The success rate of the operation is guaranteed while the test cost and time are saved.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.

Claims (3)

1. A well test design parameter correction method is characterized by comprising the following steps:
the method comprises the following steps: selecting well test design parameters according to well wall coring, well logging and well-facing test, and carrying out preliminary well test design;
step two: obtaining the yield Q and the bottom hole flowing pressure p after the flowing pressure gradient test is finishedwfAccording to Q-pwfUpdating the permeability or the skin coefficient of the initial well test design according to the corresponding relation;
step three: and the updated well testing design is used for guiding the productivity testing and pressure recovery testing processes, so that the productivity testing working system and the pressure recovery well shut-in time are more reasonable.
2. The method for correcting the design parameters of the well test according to claim 1, wherein in the first step, the selection of the design parameters of the well test is carried out according to the well wall coring, the well logging and the well-approaching test, and the method for carrying out the preliminary well test design comprises the following steps:
s1 fluid high pressure physical property parameter PVT:
for a well with a downhole fluid PVT report, directly using results made by a laboratory in the downhole fluid PVT report, wherein the specific results comprise formation pressure, temperature, density, viscosity, volume coefficient, compressibility, dew point pressure, bubble point pressure, formation water mineralization degree, deviation factors and fluid component analysis of the downhole fluid under formation conditions;
for wells which are not subjected to sampling analysis at the early stage of the test well, using high-pressure physical property parameters in a PVT report of the downhole fluid adjacent to the well at the same layer;
for a first pre-exploration well or a development well of a tested reservoir, the pressure, temperature and flow value in the result are explained by using a cable stratum test MDT in the well drilling process, other parameters use high-pressure physical property parameter values in PVT reports of other block same-layer wells with underground fluid sampling, and for the first pre-exploration well or the development well of the tested reservoir, if the construction projects in the well drilling process are few and no high-pressure physical property parameters which can be directly used exist, the high-pressure physical property parameters of the fluids of the other block same-layer wells are directly used;
s2 effective permeability:
the method for selecting the initial design permeability comprises the steps of carrying out correlation analysis on the well logging permeability and the well testing permeability of a known well logging permeability and a well testing effective permeability in a block, classifying the well logging permeability and the well testing permeability according to a sedimentary facies according to a development horizon for each well, depicting all the well logging permeability as an abscissa and the well testing effective permeability as an ordinate under the same type of sedimentary facies in a rectangular coordinate system, carrying out linear regression and polynomial regression, searching a regression relation with better correlation in the linear regression and the polynomial regression, wherein the correlation processes of the logging permeability and the well testing permeability are the same for each type of sedimentary facies, and substituting the well logging permeability into the relation according to the sedimentary facies at the testing horizon of the well and the corresponding relation of the regressed logging permeability and the well testing permeability to obtain the well testing effective permeability of the initial well testing design; for wells with poor correlation of permeability of the test well and the well, directly using the permeability of the test well as the effective permeability;
s3 reservoir effective thickness:
selecting effective thickness by using a logging interpretation result, selecting effective oil and gas layers, and removing the thickness of a dry layer; the effective thickness of the reservoir is selected according to seismic profile, a constructional diagram and logging data as references during well test design, a dominant reservoir is searched, if a production logging interpretation result is optimal, a true value of the effective thickness of the reservoir can be directly obtained, the effective thickness of the reservoir is selected, and a well test design result is influenced by a reservoir stratum coefficient kh;
s4 epidermis factor:
when the drilling fluid is soaked in a reservoir for a long time under the abnormal operation condition, the positive epidermis is given according to the soaking time and the reservoir pollution degree chart, for a normal operation well, the soaking time of the drilling fluid in the reservoir is short, the reservoir pressure is in a balanced or under-balanced state, the pollution of the drilling fluid to the reservoir is ignored and not recorded, the soaking time of the drilling fluid can be inquired from an engineering operation record, and the soaking time and the reservoir pollution degree chart are measured by a laboratory; for the measure well, the negative epidermis is given according to the evaluation and analysis result after the measure, the evaluation and analysis result after the measure is the simulation value of related professional software, and only related professional result data are used; for a normal test well, the skin factor is given 0;
s5, solving a mathematical model:
for the condition that the microcracks in the buried hill low permeability reservoir develop obviously, the reservoir characteristic curve can show the characteristics of a dual pore medium model, and the dual pore medium well testing mathematical model is solved in a Laplace space:
Figure 202378DEST_PATH_IMAGE001
(1)
in the formula:
Figure 14476DEST_PATH_IMAGE002
a Laplace space solution of bottom hole pressure; u is a Laplace space independent variable; f (u) is a function with respect to the argument u; k0(x)、K1(x) Respectively, zero order and first order imaginary vector Bessel functions; cDDimensionless well reservoir coefficients; s is the epidermis coefficient;
and for the transition section in the flowing period of the dual-pore medium, performing inversion of a Laplace space solution, and obtaining by derivation of the solution pressure:
Figure 656810DEST_PATH_IMAGE003
(2)
wherein:
Figure 933070DEST_PATH_IMAGE004
；
Figure 369868DEST_PATH_IMAGE005
in the formula: t is tDDimensionless time; cDDimensionless well reservoir coefficients; h is the reservoir thickness; r iswIs the wellbore radius; ctIs the comprehensive compression coefficient; c is a wellbore storage coefficient; kfPermeability of the fracture system; phi is porosity; omega is the energy storage ratio; lambda is the channeling coefficient, omega and lambda are the given values of the oil reservoir combined logging and logging information, and the same layer well facing logging interpretation result is used under the condition of data loss.
3. The method for correcting well testing design parameters according to claim 1, wherein the yield Q and the bottom hole flow pressure p are obtained in the second stepwfAccording to Q-pwfThe method for updating the permeability or the skin coefficient of the well test design by the corresponding relation comprises the following steps:
a1, placing a pressure gauge in the middle of the gas layer, and stably producing according to a designed working system;
a2, testing the flow pressure gradient;
a3, after the flow pressure gradient test is finished, the pressure gauge is lifted out of the wellhead to read data;
a4 obtaining production Q and bottom hole flow pressure pwfAccording to Q-pwfThe corresponding relation is as follows:
Figure 669262DEST_PATH_IMAGE006
in the formula: piIs the original formation pressure; pwfBottom hole flow pressure; q. q.sgThe well head yield; k is the effective permeability of the formation; h is the effective thickness of the stratum;
Figure 849708DEST_PATH_IMAGE007
is the reservoir condition viscosity;
Figure 980475DEST_PATH_IMAGE008
、
Figure 322595DEST_PATH_IMAGE009
respectively, gas deviation coefficient and average temperature under formation conditions; psc、TscRespectively, pressure and temperature under a gas standard state; phi is porosity; ctIs the comprehensive compression coefficient; t is time; r iswIs the radius of the well; saTo look at the skin coefficient, Sa=S+DqgS is the epidermis coefficient, D is the non-Darcy flow coefficient;
and adjusting the permeability or the skin coefficient of the preliminary well testing design to ensure that the simulated pressure value is matched with the actually measured pressure value.
CN202111291366.5A 2021-11-03 2021-11-03 Well test design parameter correction method Active CN113719271B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111291366.5A CN113719271B (en) 2021-11-03 2021-11-03 Well test design parameter correction method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111291366.5A CN113719271B (en) 2021-11-03 2021-11-03 Well test design parameter correction method

Publications (2)

Publication Number Publication Date
CN113719271A true CN113719271A (en) 2021-11-30
CN113719271B CN113719271B (en) 2022-01-21

Family

ID=78686603

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111291366.5A Active CN113719271B (en) 2021-11-03 2021-11-03 Well test design parameter correction method

Country Status (1)

Country Link
CN (1) CN113719271B (en)

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA1061246A (en) * 1975-07-14 1979-08-28 Norman G. Hortman Weight and pressure operated well testing apparatus and its method of operation
CN102418511A (en) * 2011-07-25 2012-04-18 中国石油天然气股份有限公司 Draw-down test analysis method for underground shut-in water well with low-permeability storage layer
CN102953726A (en) * 2011-08-22 2013-03-06 中国石油大学(华东) Method and device for water drive oilfield advantage channel recognition
CN104612658A (en) * 2014-11-25 2015-05-13 中国石油大学(北京) Well test analysis control system and method used for horizontal well subsection liquid producing identification
CN105569641A (en) * 2015-12-17 2016-05-11 西南石油大学 Horizontal well transient pressure rapid calculation model establishing method capable of improving near-wellbore pressure drop
CN106869918A (en) * 2017-04-27 2017-06-20 中国海洋石油总公司 Offshore field productivity test method of real-time adjustment
CN109469465A (en) * 2018-11-14 2019-03-15 中国石油天然气股份有限公司大港油田分公司 Processing method, device and the storage medium of water injection well parameter
CN111255434A (en) * 2018-11-30 2020-06-09 中国石油天然气股份有限公司 Well testing method and device for gas well and computer storage medium
CN112016753A (en) * 2020-08-31 2020-12-01 中国海洋石油集团有限公司 Metamorphic rock buried hill productivity prediction method based on ternary coupling

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA1061246A (en) * 1975-07-14 1979-08-28 Norman G. Hortman Weight and pressure operated well testing apparatus and its method of operation
CN102418511A (en) * 2011-07-25 2012-04-18 中国石油天然气股份有限公司 Draw-down test analysis method for underground shut-in water well with low-permeability storage layer
CN102953726A (en) * 2011-08-22 2013-03-06 中国石油大学(华东) Method and device for water drive oilfield advantage channel recognition
CN104612658A (en) * 2014-11-25 2015-05-13 中国石油大学(北京) Well test analysis control system and method used for horizontal well subsection liquid producing identification
CN105569641A (en) * 2015-12-17 2016-05-11 西南石油大学 Horizontal well transient pressure rapid calculation model establishing method capable of improving near-wellbore pressure drop
CN106869918A (en) * 2017-04-27 2017-06-20 中国海洋石油总公司 Offshore field productivity test method of real-time adjustment
CN109469465A (en) * 2018-11-14 2019-03-15 中国石油天然气股份有限公司大港油田分公司 Processing method, device and the storage medium of water injection well parameter
CN111255434A (en) * 2018-11-30 2020-06-09 中国石油天然气股份有限公司 Well testing method and device for gas well and computer storage medium
CN112016753A (en) * 2020-08-31 2020-12-01 中国海洋石油集团有限公司 Metamorphic rock buried hill productivity prediction method based on ternary coupling

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
国艳: "气井产能的评价研究", 《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅰ辑》 *

Also Published As

Publication number Publication date
CN113719271B (en) 2022-01-21

Similar Documents

Publication Publication Date Title
CN110321595B (en) Fault sealing evaluation method for extracting static quality coefficient by logging
CN102953726B (en) Method and device for water drive oilfield advantage channel recognition
CN104564041A (en) Low-permeability clastic rock reservoir effectiveness evaluation method based on development permeability lower limit
CN111927444B (en) Method for evaluating gas injection capacity of depleted oil-gas reservoir gas storage
CN110043254B (en) Method for obtaining stratum effective permeability based on cable stratum test data
CN113919240A (en) High-pressure gas reservoir parameter calculation method based on oil and gas well production data
CN111353205A (en) Method for calculating stratum pressure and dynamic capacity of water-producing gas well of tight gas reservoir
US20110276270A1 (en) Method to determine current gas saturation in a near-wellbore zone in a volatile oil formation
US8606523B2 (en) Method to determine current condensate saturation in a near-wellbore zone in a gas-condensate formation
CN113719271B (en) Well test design parameter correction method
CN111894570A (en) Quantitative evaluation method for flooding degree of old oil reservoir well in middle and later development periods
CN109339771B (en) Shale hydrocarbon reservoir pore pressure prediction method and system
CN116384085A (en) Compact oil and gas reservoir capacity splitting method
RU2752802C1 (en) Method for determining porosity and permeability characteristics of reservoir and method for increasing petroleum recovery thereby
CN109994161B (en) Method for calculating organic carbon content of stratum by combining trend baseline method with dynamic linkage method
Proett et al. Low Permeability Interpretation Using a New Wireline Formation Tester" Tight Zone" Pressure Transient Analysis
CN114647913A (en) Maximum level principal ground stress acquisition method based on Mohr-Coulomb criterion
Nie et al. Time-tracking tests and interpretation for a horizontal well at different wellbore positions
CN113622903B (en) Reservoir reconstruction method and device
US20230259670A1 (en) Permeability modeling in a reservoir simulation model using dynamic pressure transient analysis
CN111487157B (en) Shale gas loss calculation method based on-site desorption and nuclear magnetic resonance combined measurement
Jochen et al. Reservoir characterization of an openhole cavity completion using production and well test data analysis
Peng et al. Effects of Near-Wellbore Supercharging and Hydro-Mechanical Coupling on Pressure Response for Formation Testing While Drilling
CN113935089A (en) Bubble point pressure correction model based on conjugate gradient method
CN106677764B (en) Method for calculating pressure difference in production of stress sensitivity gas reservoir test

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
GR01 Patent grant
GR01 Patent grant