CN105931125B - Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well - Google Patents

Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well Download PDF

Info

Publication number
CN105931125B
CN105931125B CN201610258620.4A CN201610258620A CN105931125B CN 105931125 B CN105931125 B CN 105931125B CN 201610258620 A CN201610258620 A CN 201610258620A CN 105931125 B CN105931125 B CN 105931125B
Authority
CN
China
Prior art keywords
section
oil layer
drilling
horizontal
logging
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.)
Active
Application number
CN201610258620.4A
Other languages
Chinese (zh)
Other versions
CN105931125A (en
Inventor
雷启鸿
王冲
樊建明
赵国玺
时建超
薛婷
陈小东
张瀚丹
郭路
喻晓琳
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.)
Petrochina Co Ltd
Original Assignee
Petrochina 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 Petrochina Co Ltd filed Critical Petrochina Co Ltd
Priority to CN201610258620.4A priority Critical patent/CN105931125B/en
Publication of CN105931125A publication Critical patent/CN105931125A/en
Application granted granted Critical
Publication of CN105931125B publication Critical patent/CN105931125B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02Agriculture; Fishing; Forestry; Mining
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Health & Medical Sciences (AREA)
  • Development Economics (AREA)
  • Agronomy & Crop Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Marine Sciences & Fisheries (AREA)
  • Mining & Mineral Resources (AREA)
  • Primary Health Care (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Animal Husbandry (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Geophysics And Detection Of Objects (AREA)
  • Investigation Of Foundation Soil And Reinforcement Of Foundation Soil By Compacting Or Drainage (AREA)

Abstract

The invention provides a yield prediction method for a compact oil subsection multi-cluster volume fracturing horizontal well, which is characterized in that on the basis of analysis of yield influence factors of a compact oil field development test, the change of horizontal oil content of a horizontal section is reflected by a horizontal heterogeneous coefficient of an oil layer, the size of the oil content of the horizontal section obtained by logging is reflected by the area of an envelope surface of a standard gas logging full hydrocarbon value of the oil layer along the process, the change of permeability of the reservoir is reflected by logging interpretation permeability, and the development degree of an artificial fracture is comprehensively reflected by a logging brittleness index and the inflow amount of the artificial fracture, so that the yield of the compact oil subsection multi-cluster volume fracturing horizontal well is well predicted, the investment risk in the compact oil scale development is reduced, and the aim of improving the yield benefit is fulfilled.

Description

Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well
Technical Field
The invention belongs to the technical field of oilfield development, and particularly relates to a yield prediction method for a compact oil staged multi-cluster volume fracturing horizontal well.
Background
The compact oil refers to oil gas gathering formed by clamping or being close to a compact reservoir stratum of a high-quality hydrocarbon source rock stratum system and not carrying out large-scale long-distance migration, generally has no fracturing and natural capacity, and the staged multi-cluster volume fracturing development of the horizontal well becomes a main means for developing the compact oil at present; the most obvious difference between the development of the compact oil horizontal well and the development of the low-permeability reservoir horizontal well in the past is that the investment of a single well is large, the construction period is long, the investment risk in the scale development of the compact oil is reduced, the goal of improving the construction benefit is achieved, the yield prediction of the staged multi-cluster volume fracturing horizontal well becomes a hot point problem of the compact oil development, and meanwhile, the yield prediction is also a difficult problem and is mainly reflected in the following 2 aspects.
1. The transverse oil-containing property of a compact oil reservoir changes greatly, the yield of a horizontal well and the transverse oil-containing property have a close relation, and the change of the transverse oil-containing property heterogeneity is difficult to reflect by the existing horizontal well logging interpretation model and the testing method. The horizontal well is different from a vertical well, the horizontal well penetrates through a stratum nearly horizontally, media around a well hole are not radially symmetrical and are influenced by gravity factors, the logging state of an instrument is usually eccentric, the eccentricity has different degrees of influence on measurement of various logging instruments, and most notably, under the condition of equivalent modification scale, the correlation between oil saturation and yield of logging interpretation is poor, and influence factors sensitive to the yield need to be screened.
2. The rock brittleness index of a compact reservoir is larger, the reservoir reconstruction scale is larger, the formed fracture network is more complex, the technology for describing the length, the width and the height of the fracturing fracture of the artificial fracture network is not mature, and the result of the underground micro-seismic monitoring method which is the conventional artificial fracture detection technology is only a micro-seismic signal parameter and cannot represent the real fracture form.
From the aspect of literature investigation on the condition of a fractured horizontal well yield prediction method, the existing prediction method can be summarized into two types: one is a numerical simulation method, and the other is a theoretical analytical model prediction method. However, no matter a numerical simulation method or a theoretical analytical model prediction method is adopted, when the yield is predicted, the precision of the existing method is poor when the method is applied to a mine field due to the fact that a compact oil subsection multi-cluster volume fracturing horizontal well artificial fracture parameter description technology is not mature and the problem that the oil saturation cannot reflect the change of the horizontal well transverse oil content through conventional well logging explanation. The method is characterized in that parameters sensitive to actual yield change of the compact oil horizontal well are screened from three aspects of oiliness, permeability and fracture development degree which affect the segmented multi-cluster volume fracturing yield of the compact oil horizontal well.
Disclosure of Invention
The invention aims to solve the problems that a numerical simulation method and a theoretical analysis method are difficult to better reflect the large change of the transverse oil content of a compact oil reservoir and the difficulty in describing the development degree of an artificial fracture.
Therefore, the invention provides a method for predicting the yield of a compact oil staged multi-cluster volume fracturing horizontal well, which comprises the following steps of:
step 1) obtaining the horizontal heterogeneous coefficient HE of an oil layer after the drilling of the horizontal well is finishedf
Step 2) obtaining the logging permeability enveloping surface area K' of the horizontal section in-process oil layer according to the permeability of the horizontal section in-process oil layer in the logging result;
step 3) obtaining a standard gas logging total hydrocarbon value Q for eliminating drilling time and inlet drilling fluid flow according to real-time logging results in the drilling process of the horizontal wellTObtaining the full hydrocarbon value enveloping surface area Q of the horizontal well section along the on-way oil layer standard gas logging by applying definite integralT';
Step 4), calculating the rock brittleness index by using a Barnett shale brittleness index formula through longitudinal wave time difference, transverse wave time difference and rock volume density value;
step 5) according to the rock brittleness index obtained through calculation, applying a definite integral principle to obtain the oil layer brittleness index enveloping surface area BI' of the horizontal segment along the process;
step 6) calculating the total underground liquid amount L of the single well according to the accumulated summation of the underground liquid amounts of each section in the segmented multi-cluster volume fracturing processv
Step 7) obtaining a yield Q prediction formula of the segmented multi-cluster volume fracturing horizontal well:
Q=1.628*Ln(HEf×K'×QT'×BI'×LV)-50.717。
step 1) the horizontal heterogeneous coefficient HE of the oil layerfTotal length L of oil layer for drilling water level sectionoWith discontinuous oil layer sectionThe ratio of the number N:
in the formula, HEfThe horizontal heterogeneous coefficient of the oil layer is m/section; l isoThe total length m of the oil layer in the water level section is drilled; n is the number of oil layer sections in the drilling horizontal section; l isiFor drilling the length of the ith oil layer section m in the water-level section.
Step 2), calculating the area K' of the logging permeability enveloping surface of the oil layer along the horizontal section by the following formula:
k' is the area of a permeability enveloping surface of a horizontal section along in-process oil layer logging, and mD.m;
kijthe permeability mD at the jth sampling point in the ith oil layer section in the drilling water horizontal section is obtained;
and delta l is the logging sampling interval, m.
Step 3) measuring the total hydrocarbon value enveloping surface area Q of the standard gas of the in-situ oil layer at the horizontal well sectionT' calculated by the following formula:
wherein Q isTThe area of an envelope surface of a standard gas measurement total hydrocarbon value of an in-situ oil layer at a horizontal section,%. m; qTijFor drilling in water levelThe corresponding standard gas measurement total hydrocarbon value at the jth sampling point of the ith oil layer section in the section,%;
step 4), calculating the rock brittleness index according to the following formula:
wherein,
in the formula, BIijLogging brittleness index,%, corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section; delta EijThe normalized Young modulus corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; Δ μijThe normalized Poisson's ratio corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; eijFor drilling the corresponding Young's modulus at the jth sampling point of the ith oil interval in the water-level segment, 104MPa;μijThe Poisson ratio corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; rhobijCorresponding rock volume density, g/cm, at the jth sampling point of the ith oil layer section in the drilling water horizontal section3;ΔtsijThe transverse wave time difference of the rock corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is [ mu ] s/m; Δ tpijAnd (3) drilling longitudinal wave time difference (mu s/m) of the rock corresponding to the jth sampling point of the ith oil layer section in the water level section.
Step 5), obtaining the area BI' of the on-way oil layer brittleness index enveloping surface of the horizontal section through the following formula:
the total amount of the ground liquid entering the single well in the step 6)Wherein L isvTotal amount of ground liquid per well m3;LviThe volume of the i-th section of the staged multi-cluster fracturing is measured in the ground3
The standard gas measured total hydrocarbon value QTGas logging full hydrocarbon value q obtained by real-time logging in the process of drilling horizontal well through inverse trigonometric function methodtAnd (3) correcting to obtain:
in the formula, vijFor drilling the actual drilling fluid flow m at the jth sampling point of the ith oil layer section in the water level section3/min;tijThe actual drilling time is min/m at the jth sampling point of the ith oil layer section in the drilling water horizontal section; v isoFor block standard drilling fluid inlet, m3/min;toIn the standard drilling time of the block, min/m; q. q.stijAnd (4) measuring the total hydrocarbon value while drilling at the jth sampling point of the ith oil layer section in the drilling water horizontal section.
The transverse wave time difference Deltat of the rocksijWhen the calculation formula is used for logging, only the longitudinal wave time difference delta t is measuredpijThe test was performed without testing the cross-wave moveout.
The invention has the beneficial effects that: on the basis of analysis of yield influence factors of development tests of compact oil fields, the method provided by the invention reflects the change of horizontal oil content of a horizontal section by using a horizontal heterogeneous coefficient of an oil layer, reflects the size of the oil content by using the enveloping area of a full hydrocarbon value of a horizontal section obtained by logging along a process oil layer standard gas logging, reflects the change of reservoir permeability by using logging interpretation permeability, and comprehensively reflects the development degree of artificial fractures by using a logging brittleness index and the inflow amount of the artificial fractures into the ground, so that the yield of a compact oil segmented multi-cluster volume fracturing horizontal well is well predicted, the investment risk in the scale development of compact oil is reduced, and the aim of improving the yield benefit is fulfilled.
The following will be described in further detail with reference to the accompanying drawings.
Drawings
FIG. 1 is the horizontal heterogeneous coefficients HE of the reservoirfA relation curve with the daily yield of a single well of the horizontal well;
FIG. 2 is a curve of average permeability k at a single well fracture versus daily production of a single well of a horizontal well;
FIG. 3 is the average log porosity at a single well fractureA relation curve with the daily yield of a single well of the horizontal well;
FIG. 4 average log oil saturation S at single well fractureoA relation curve with the daily yield of a single well of the horizontal well;
FIG. 5 is a relation curve of average rock brittleness index BI at a single well fracture and daily production of a single well of a horizontal well;
FIG. 6 average Standard gas Total Hydrocarbon number Q at fractureTA relation curve with the daily yield of a single well of the horizontal well;
FIG. 7 is a plot of log permeability envelope area K' versus daily production for a single well of a horizontal well;
FIG. 8 is a plot of the log porosity envelope area Φ' versus the daily production of a single well of a horizontal well;
FIG. 9 is the logging oil saturation envelope surface area So' a curve relating the daily production of a single well of a horizontal well;
FIG. 10 is a plot of well log brittleness index envelope area BI' versus daily production for a single well of a horizontal well;
FIG. 11 is a plot of the standard gas log total hydrocarbon number envelope area QT' a curve relating the daily production of a single well of a horizontal well;
FIG. 12 staged multi-cluster volume fracturing fluid volume in the earth LvA relation curve with the daily yield of a single well of the horizontal well;
FIG. 13 is a curve of the relationship between the number STA of the segmented multi-cluster volume fracture sections of the well and the daily yield of a single well of the horizontal well;
FIG. 14 is a curve of the average sand adding amount SAN of the single-well staged multi-cluster volume fracturing and the daily yield of a single well of a horizontal well;
FIG. 15 is a graph of average displacement PR of single well staged multi-cluster volume fracturing versus daily production of a single well of a horizontal well;
FIG. 16 is a plot of the average sand ratio PC for single well staged multiple cluster volume fracturing versus the daily production for a single well of a horizontal well;
FIG. 17 is a plot of envelope coefficients versus daily production for a single well of a horizontal well;
FIG. 18 is a GP47-64 well logging interpretation single well card.
Detailed Description
Example 1:
the embodiment provides a yield prediction method for a compact oil staged multi-cluster volume fracturing horizontal well, which comprises the following steps of:
step 1) levelingObtaining the horizontal heterogeneous coefficient HE of an oil layer after well drilling is finishedf
Step 2) obtaining the logging permeability enveloping surface area K' of the horizontal section in-process oil layer according to the permeability of the horizontal section in-process oil layer in the logging result;
step 3) obtaining a standard gas logging total hydrocarbon value Q for eliminating drilling time and inlet drilling fluid flow according to real-time logging results in the drilling process of the horizontal wellTObtaining the full hydrocarbon value enveloping surface area Q of the horizontal well section along the on-way oil layer standard gas logging by applying definite integralT';
Step 4), calculating the rock brittleness index by using a Barnett shale brittleness index formula through longitudinal wave time difference, transverse wave time difference and rock volume density value;
step 5) according to the rock brittleness index obtained through calculation, applying a definite integral principle to obtain the oil layer brittleness index enveloping surface area BI' of the horizontal segment along the process;
step 6) calculating the total underground liquid amount L of the single well according to the accumulated summation of the underground liquid amounts of each section in the segmented multi-cluster volume fracturing processv
Step 7) obtaining a yield Q prediction formula of the segmented multi-cluster volume fracturing horizontal well:
Q=1.628*Ln(HEf×K'×QT'×BI'×LV)-50.717。
the method reflects the size of oil content by using the enveloping surface area of the full hydrocarbon value of the horizontal segment along the in-process oil layer standard gas logging obtained by logging, reflects the change of reservoir permeability by using logging interpretation permeability, comprehensively reflects the development degree of artificial fractures by using logging brittleness indexes and the amount of liquid entering the ground of the artificial fractures, and guides to establish the yield prediction method of the compact oil segmented multi-cluster volume fracturing horizontal well.
Example 2:
screening of yield sensitive parameters of compact oil horizontal well
The influence factors influencing the segmented multi-cluster volume fracturing yield of the compact oil horizontal well comprise geological factors and engineering factors. Reservoir oiliness, reservoir permeability and reservoir seam network formation difficulty are considered in geological factors, wherein the reservoir oiliness can be characterized by 4 parameters of an oil layer transverse heterogeneous coefficient, a logging gas logging total hydrocarbon value, a logging oil saturation and a logging porosity, the reservoir permeability is characterized by a logging permeability, and the reservoir seam network formation difficulty is characterized by a rock brittleness index; engineering factors mainly influence the development degree of a reservoir fracture network after volume fracturing modification, and mainly comprise 5 parameters of the ground liquid entering amount, the number of the artificial fracturing modification sections, the sand adding amount, the discharge amount and the sand ratio;
the method comprises the following steps: geological factor screening
(1) Horizontal heterogeneous coefficient HE of reservoirf: according to the well logging interpretation conclusion, the length L of the oil layer encountered by the horizontal section of each sample horizontal well is countedoAnd the number N of oil layer sections of the horizontal section to obtain the horizontal heterogeneous coefficient HE of the oil layer of each sample horizontal wellf
(2) Calculating horizontal heterogeneous coefficient HE of sample horizontal well according to formula (1)fMaking a scatter diagram of the transverse heterogeneous coefficient and the yield of the corresponding horizontal well, wherein the correlation between a regression formula and a sample point is better as shown in figure 1, so that the transverse heterogeneous coefficient of an oil layer is taken as a main geological parameter influencing the yield factor of the compact oil horizontal well;
the method comprises the steps that geological parameters at a horizontal section fracturing position represent parameters of the whole horizontal well for analyzing influence factors of single well yield of a conventional horizontal well, and for fracturing a compact oil horizontal well with a large discharge volume, the influence factors of the compact oil horizontal well are analyzed by applying the same parameter statistical method;
(3) average logging permeability k at the single well fracture;
(4) average logging porosity at single well fracture
(5) Average logging oil saturation S at single well fractureo
(6) Average standard gas logging total hydrocarbon value Q at single well fractureT
Gas logging total hydrocarbon value q obtained by real-time logging in the drilling process of horizontal welltCorrecting and correcting by using an inverse trigonometric function method to obtain a standard gas-logging total hydrocarbon value Q for eliminating the drilling time and the inlet drilling fluid flowT
Standard gas survey total hydrocarbon number
(7) Average rock brittleness index BI at a single well fracture;
the rock brittleness index BI cannot be directly obtained through a logging curve, and a Barnett shale brittleness index calculation formula is used for calculating the brittleness index of the long-7 compact reservoir according to the longitudinal wave time difference, the transverse wave time difference and the rock volume density value;
index of brittleness
Normalized Young's modulus
Normalized Poisson's ratio
Young's modulus
Poisson ratio
The method is characterized in that an empirical formula which is suitable for gas-free sandstone or argillaceous sandstone formations and is used for estimating transverse waves is used for calculating to obtain the formation transverse wave time difference delta ts
(8) Calculating average geological parameters at the cracks of the horizontal well according to formulas (1) to (6), and making a scatter diagram of each geological parameter and the daily yield of the single well of the horizontal well, as shown in fig. 2 to 6, as can be seen from the correlation coefficient of the regression trend line in table 1, the correlation between the average value of each geological parameter crack and the yield is poor, so that the relation between the area of a geological parameter envelope surface of the heterogeneity of an oil layer along the whole horizontal section and the yield is analyzed and considered;
(9) according to the permeability of an oil layer in a horizontal section in a logging interpretation conclusion after the drilling of the horizontal well is finished, applying a definite integral principle to obtain the logging permeability enveloping surface area K' of the oil layer in the horizontal section along the way:
(10) according to the porosity of an oil layer at a horizontal section in a logging interpretation conclusion after the drilling of the horizontal well is finished, applying a definite integral principle to obtain the logging porosity enveloping surface area phi' of the oil layer at the horizontal section along the way:
(11) according to the oil saturation of the oil reservoir in the horizontal section in the well logging interpretation conclusion after the well drilling of the horizontal well is finished, the oil saturation enveloping surface area S of the logging oil saturation of the oil reservoir in the horizontal section along the way is obtained by applying the definite integral principleo':
(12) Gas logging total hydrocarbon value q obtained by real-time logging in the drilling process of horizontal welltCorrecting and correcting by using an inverse trigonometric function method to obtain a standard gas-logging total hydrocarbon value Q for eliminating the drilling time and the inlet drilling fluid flowTObtaining the area of the envelope surface of the standard gas-measured total hydrocarbon value of the oil layer along the horizontal section by applying the definite integral principleQT':
Standard gas survey total hydrocarbon number
The area of the envelope surface of the full hydrocarbon value of the horizontal section along the standard gas logging of the in-situ oil layer is as follows:
(13) the rock brittleness index BI cannot be directly obtained through a logging curve, and a Barnett shale brittleness index calculation formula is used for calculating the brittleness index of the long-7 compact reservoir according to the longitudinal wave time difference, the transverse wave time difference and the rock volume density value;
index of brittleness of rock
Normalized Young's modulus
Normalized Poisson's ratio
Young's modulus
Poisson ratio
The application is suitable for use withoutThe gas sandstone or argillaceous sandstone stratum is used for the empirical formula calculation of the shear wave estimation to obtain the stratum shear wave time difference delta ts
According to the rock brittleness index obtained through calculation, obtaining the area BI' of the oil layer logging index enveloping surface of the horizontal segment along the way by applying a definite integral principle;
(14) the sampling intervals of the logging series used in the field of the Changqing are all 0.125m, i.e. Δ l is 0.125m, so the equations (7) to (11) can be simplified into the following forms:
(15) and (4) calculating the area of the in-situ oil layer envelope surface of the horizontal section of the geological parameter of each sample horizontal well according to the formulas (12) to (16), and making scatter diagrams of the parameters and the daily yield of the single well (figures 7 to 13). Obtaining the correlation coefficient R of the trend line according to a regression formula2(see table 1), it can be seen that the relation between the area of each geological parameter envelope and the daily production of a single well is better than the relation between the average value of the fracture and the daily production of a single well. Meanwhile, the area of an oil layer logging permeability enveloping surface, the area of a standard gas logging total hydrocarbon value enveloping surface and the area of a brittleness index enveloping surface which have good correlation are screened out to be used as main factors influencing the yield of the compact oil horizontal well.
Step two: engineering factor screening
Engineering factors mainly influence the development degree of a reservoir fracture network after volume fracturing transformation, and mainly comprise 5 parameters of the ground liquid entering amount, the number of artificial fracture sections, the sand adding amount, the discharge amount and the sand ratio;
(16) single-well staged multi-cluster volume fracturing ground entering liquid quantity Lv
(17) The method comprises the following steps that (1) the number STA of multiple volume fracture sections is segmented in a single well;
STA=n (18)
(18) the average sand adding amount SAN of the single-well subsection multi-cluster volume fracturing;
(19) the average displacement PR of the single-well staged multi-cluster volume fracturing;
(20) single-well subsection multi-cluster volume fracturing average sand ratio PC;
according to the single-well engineering parameters of each sample horizontal well calculated by the formulas (17) - (21), making a scatter diagram (fig. 12-16) of each engineering parameter and the daily yield of each well, and preferably selecting the single-well earth-entering liquid amount as a main factor influencing the yield of the compact oil horizontal well according to the size of the correlation coefficient (table 1);
(II) regression of compact oil horizontal well yield formula
Analyzing the relation between each influence factor and the daily yield of a single well, and obtaining a yield prediction formula of the compact oil subsection multi-cluster volume fracturing horizontal well by 5 parameter regression as shown in figure 17;
Q=1.628*Ln(HEf×K'×QT'×BI'×LV)-50.717 (22)
q is the volume fractured horizontal well yield, t/d.
TABLE 1 correlation coefficient of tight oil horizontal well yield influencing factors and yield scatter plots
Example 3:
the water combining length 7 is controlled by multiple sources in the west, the southwest and the south, the southwest source is taken as the main source, and two types of sedimentary facies such as delta and lake are developed; mainly develop the nepheloid rock reservoir formed by collapse of the front edge of the delta. The turbid water channel sand is used as the skeleton sand body of the region and distributed in an lobate shape and a block shape, the sand body is large in thickness, the oil layer is relatively stable in distribution, the thickness is large, the oil reservoir has a large scale, and the resource potential is large.
GP47-64 is a water-length-combined 7-reservoir one-mouth development horizontal well (figure 18), the length of the horizontal section is 680m, oil-encountering drilling intervals are 647m, the number of the oil-encountering drilling intervals is 7, a hydraulic jet annulus sand-adding volume fracturing transformation mode is adopted, and the amount of liquid entering the ground is 3550m3The area of the oil layer section logging permeability enveloping surface is 143.8 mD.m, the area of the gas logging total hydrocarbon value enveloping surface is 19137.1%. m, the area of the brittleness index enveloping surface is 34938.2%. m, and the transverse heterogeneous coefficient of the oil layer is 96.3 m/section. According to a compact oil horizontal well yield prediction formula, the daily yield of each well of GP47-64 wells is calculated to be 11.1t/d, the actual daily yield of each well is 10.5t/d, the prediction error is 5.9%, the effect is good, and the specific calculation process is shown in the GP47-64 yield prediction process.
GP47-64 yield prediction process:
the method comprises the following steps: calculating horizontal heterogeneous coefficient HE of oil reservoirf
Step two: calculating the area of the logging permeability enveloping surface of the horizontal section along the in-situ oil layer (see table 2):
TABLE 2 horizontal section in-situ oil layer logging permeability enveloping surface area calculation step
Step three: calculating the area of the envelope surface of the standard gas logging total hydrocarbon value of the horizontal section along the in-situ oil layer (see table 3):
TABLE 3 horizontal section calculation step of full hydrocarbon value envelope area along in-situ oil layer standard gas logging
Step four: calculating the area of the brittleness index enveloping surface of the horizontal section along the in-situ oil layer logging (see table 4):
TABLE 4 calculation step of in-flight oil layer brittleness index envelope surface area
Step five: according to the volume of the segmented multi-clusterCalculating the total underground liquid quantity L of the single well by the underground liquid quantity of each section in the cracking processv
Step six: calculating the yield of GP 47-64:
Q=1.628*Ln(HEf×K'×QT'×BI'×LV)-50.717
=1.628×Ln(96.3×143.8×19137.1×34938.2×3550)-50.717
=11.1t/d
the actual yield of GP47-64 is 10.5t/d, and the error between the calculated value and the actual value is 5.9%.
The above examples are merely illustrative of the present invention and should not be construed as limiting the scope of the invention, which is intended to be covered by the claims and any design similar or equivalent to the scope of the invention.

Claims (9)

1. A yield prediction method for a compact oil staged multi-cluster volume fracturing horizontal well is characterized by comprising the following steps of:
step 1) obtaining the horizontal heterogeneous coefficient HE of an oil layer after the drilling of the horizontal well is finishedf
Step 2) obtaining the logging permeability enveloping surface area K' of the horizontal section in-process oil layer according to the permeability of the horizontal section in-process oil layer in the logging result;
step 3) obtaining the elimination drilling time according to the real-time logging result in the drilling process of the horizontal wellStandard gas logging total hydrocarbon number Q with inlet drilling fluid flowTObtaining the full hydrocarbon value enveloping surface area Q of the horizontal well section along the on-way oil layer standard gas logging by applying definite integralT';
Step 4), calculating the rock brittleness index by using a Barnett shale brittleness index formula through longitudinal wave time difference, transverse wave time difference and rock volume density value;
step 5) according to the rock brittleness index obtained through calculation, applying a definite integral principle to obtain the oil layer brittleness index enveloping surface area BI' of the horizontal segment along the process;
step 6) calculating the total underground liquid amount L of the single well according to the accumulated summation of the underground liquid amounts of each section in the segmented multi-cluster volume fracturing processv
Step 7) obtaining a yield Q prediction formula of the segmented multi-cluster volume fracturing horizontal well:
Q=1.628*Ln(HEf×K'×QT'×BI'×LV)-50.717。
2. the method for predicting the yield of the compact oil staged multi-cluster volume fractured horizontal well according to claim 1, wherein the method comprises the following steps: step 1) the horizontal heterogeneous coefficient HE of the oil layerfTotal length L of oil layer for drilling water level sectionoThe ratio of the number of discontinuous oil layer sections to N:
in the formula, HEfThe horizontal heterogeneous coefficient of the oil layer is m/section; l isoThe total length m of the oil layer in the water level section is drilled; n is the number of discontinuous oil layer sections; l isiFor drilling the length of the ith oil layer section m in the water-level section.
3. The method for predicting the yield of the compact oil staged multi-cluster volume fractured horizontal well according to claim 1, wherein the method comprises the following steps: step 2), calculating the area K' of the logging permeability enveloping surface of the oil layer along the horizontal section by the following formula:
k' is the area of a permeability enveloping surface of a horizontal section along in-process oil layer logging, and mD.m;
n is the number of discontinuous oil layer sections; k is a radical ofijThe permeability mD at the jth sampling point in the ith oil layer section in the drilling water horizontal section is obtained; and delta l is the logging sampling interval, m.
4. The method for predicting the yield of the compact oil staged multi-cluster volume fractured horizontal well according to claim 1, wherein the method comprises the following steps: step 3) measuring the total hydrocarbon value enveloping surface area Q of the standard gas of the in-situ oil layer at the horizontal well sectionT' calculated by the following formula:
wherein Q isTThe area of an envelope surface of a standard gas measurement total hydrocarbon value of an in-situ oil layer at a horizontal section,%. m; n is the number of discontinuous oil layer sections; qTijMeasuring the total hydrocarbon value% of the standard gas corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section; delta l is the logging sampling interval, m; v. ofijFor drilling the actual drilling fluid flow m at the jth sampling point of the ith oil layer section in the water level section3/min;tijThe actual drilling time is min/m at the jth sampling point of the ith oil layer section in the drilling water horizontal section; v. ofoFor block standard drilling fluid inlet, m3/min;toIn the standard drilling time of the block, min/m; q. q.stijAnd (4) measuring the total hydrocarbon value while drilling at the jth sampling point of the ith oil layer section in the drilling water horizontal section.
5. The method for predicting the yield of the compact oil staged multi-cluster volume fractured horizontal well according to claim 1, wherein the method comprises the following steps: step 4), calculating the rock brittleness index according to the following formula:
wherein,
in the formula, BIijLogging brittleness index,%, corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section; delta EijDrilling a normalized Young modulus corresponding to the jth sampling point of the ith oil layer section in the water level section, wherein the normalized Young modulus is dimensionless; Δ μijThe normalized Poisson's ratio corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; eijDrilling the corresponding Young's modulus at the jth sampling point of the ith oil layer section in the water level section, 104MPa;μijThe Poisson ratio corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is dimensionless; rhobijCorresponding rock volume density, g/cm, at the jth sampling point of the ith oil layer section in the drilling water horizontal section3;ΔtsijThe transverse wave time difference of the rock corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section is [ mu ] s/m;for drilling the longitudinal wave time difference, mu s-m。
6. The method for predicting the yield of the compact oil staged multi-cluster volume fractured horizontal well according to claim 1, wherein the method comprises the following steps: step 5), obtaining the area BI' of the on-way oil layer brittleness index enveloping surface of the horizontal section through the following formula:
wherein N is the number of discontinuous oil layer sections; BI (BI)ijLogging brittleness index,%, corresponding to the jth sampling point of the ith oil layer section in the drilling water horizontal section; and delta l is the logging sampling interval, m.
7. The method for predicting the yield of the compact oil staged multi-cluster volume fractured horizontal well according to claim 1, wherein the method comprises the following steps: the total amount of the ground liquid entering the single well in the step 6)Wherein L isvTotal amount of ground liquid per well m3;LviThe volume of the i-th section of the staged multi-cluster fracturing is measured in the ground3
8. The method for predicting yield of compact oil staged multi-cluster volume fractured horizontal well according to claim 4, wherein the standard gas-logging total hydrocarbon value QTGas logging full hydrocarbon value q obtained by real-time logging in the process of drilling horizontal well through inverse trigonometric function methodtAnd (3) correcting to obtain:
in the formula, vijFor drilling the actual drilling fluid flow m at the jth sampling point of the ith oil layer section in the water level section3/min;tijThe actual drilling time is min/m at the jth sampling point of the ith oil layer section in the drilling water horizontal section; v isoFor block standard drilling fluid inlet, m3/min;toIn the standard drilling time of the block, min/m; q. q.stijAnd (4) measuring the total hydrocarbon value while drilling at the jth sampling point of the ith oil layer section in the drilling water horizontal section.
9. The method for predicting yield of the compact oil staged multi-cluster volume fractured horizontal well according to claim 5, wherein the method comprises the following steps: the transverse wave time difference Deltat of the rocksijWhen the calculation formula is used for logging, only the longitudinal wave time difference is measuredThe test was performed without testing the cross-wave moveout.
CN201610258620.4A 2016-04-22 2016-04-22 Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well Active CN105931125B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610258620.4A CN105931125B (en) 2016-04-22 2016-04-22 Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610258620.4A CN105931125B (en) 2016-04-22 2016-04-22 Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well

Publications (2)

Publication Number Publication Date
CN105931125A CN105931125A (en) 2016-09-07
CN105931125B true CN105931125B (en) 2019-09-03

Family

ID=56837019

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610258620.4A Active CN105931125B (en) 2016-04-22 2016-04-22 Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well

Country Status (1)

Country Link
CN (1) CN105931125B (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108194077B (en) * 2017-12-15 2021-06-11 中国石油集团川庆钻探工程有限公司 Gas logging total hydrocarbon correction method
CN108763751A (en) * 2018-05-28 2018-11-06 中石化石油工程技术服务有限公司 The bearing calibration of total hydrocarbon in gas logging data in a kind of petroleum geology well logging
CN109101773A (en) * 2018-09-27 2018-12-28 北京科技大学 Fine and close grease horizontal well solid seam net cluster network pressure splits optimization method
CN109882163A (en) * 2019-03-27 2019-06-14 中国石油大学(华东) A kind of PRODUCTION FORECASTING METHODS for compact oil reservoir pressure break horizontal well
CN109977586B (en) * 2019-04-04 2022-05-13 中国石油大学(华东) Sectional clustering method and device for volume fractured horizontal well
CN110442835B (en) * 2019-06-27 2023-04-28 大庆油田有限责任公司 Method for predicting capacity of sand river subgroup sandstone reservoir before vertical well pressure

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103266881A (en) * 2013-05-22 2013-08-28 中国石化集团华北石油局 Method for predicting yield of compact hypotonic gas field multistage fracturing horizontal well
CN105404735A (en) * 2015-11-10 2016-03-16 中国石油天然气股份有限公司 Quantitative evaluation method for contribution rate of fractures and matrix to single well yield of ultra-low permeability reservoir

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9341557B2 (en) * 2012-11-14 2016-05-17 Kuwait Oil Company (K.S.C.) Method and system for permeability calculation using production logs for horizontal wells, using a downhole tool

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103266881A (en) * 2013-05-22 2013-08-28 中国石化集团华北石油局 Method for predicting yield of compact hypotonic gas field multistage fracturing horizontal well
CN105404735A (en) * 2015-11-10 2016-03-16 中国石油天然气股份有限公司 Quantitative evaluation method for contribution rate of fractures and matrix to single well yield of ultra-low permeability reservoir

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
低渗透油藏压裂水平井井网形式研究;屈雪峰 等;《科学技术与工程》;20131231;第13卷(第35期);10628-10632
鄂尔多斯盆地长7致密油水平井体积压裂开发效果评价及认识;樊建明 等;《中国石油大学学报(自然科学版)》;20150831;第39卷(第4期);103-110

Also Published As

Publication number Publication date
CN105931125A (en) 2016-09-07

Similar Documents

Publication Publication Date Title
CN105931125B (en) Method for predicting yield of compact oil staged multi-cluster volume fracturing horizontal well
CN109441422B (en) Shale gas well spacing optimization mining method
CN113901681B (en) Three-dimensional compressibility evaluation method for dual desserts of shale gas reservoir in whole life cycle
CN110321595B (en) Fault sealing evaluation method for extracting static quality coefficient by logging
CN105468886B (en) The method for calculating strata pressure based on petrophysical parameters
RU2661489C1 (en) Method of integrating initial data to update filtration structure of non-uniform carbonate reservoirs
CN103857876A (en) System and method for performing wellbore fracture operations
CN110456412B (en) Method for identifying fluid saturation of carbonate reservoir based on post-stack seismic data
CN104863577A (en) Method for forecasting formation pore pressure by utilizing propagation time of seismic longitudinal waves
CN107590550A (en) The method evaluated and predicted about super-low permeability reservoir oil field production capacity
Hui et al. Intricate unconventional fracture networks provide fluid diffusion pathways to reactivate pre-existing faults in unconventional reservoirs
CN107829731B (en) Clay alteration volcanic porosity correction method
Ling et al. Comparisons of Biot's coefficients of bakken core Samples measured by three methods
CN109509111A (en) The prediction technique and system of prospect pit strata pressure
CN109458176A (en) The prediction technique and its application of carbonate reservoir pressure
CN112145165B (en) Microcrack-pore type reservoir dynamic and static permeability conversion method
Sabea et al. Geological model of the Khabour Reservoir for studying the gas condensate blockage effect on gas production, Akkas Gas Field, Western Iraq
Xu et al. Fracability evaluation method for tight sandstone oil reservoirs
CN109339771B (en) Shale hydrocarbon reservoir pore pressure prediction method and system
Deng et al. A new index used to characterize the near-wellbore fracture network in naturally fractured gas reservoirs
RU2585296C1 (en) Method of determining drained hydraulic fracturing crack width and degree of sedimentation of proppant therein
Worthington et al. Optimizing the value of reservoir simulation through quality-assured initialization
Robinson et al. Hydraulic fracturing research in East Texas: third GRI staged field experiment
RU2012021C1 (en) Method for determining crumbling porosity of rocks
Abdideh et al. Modeling reference fracture pressures to design hydraulic fracture operations using well logging data

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant