CN105931125B - A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section - Google Patents

A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section 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
well
horizontal segment
oil
horizontal
section
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.)
China Petroleum and Natural Gas Co Ltd
Original Assignee
China Petroleum and Natural Gas 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 Petroleum and Natural Gas Co Ltd filed Critical China Petroleum and Natural Gas 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 present invention provides a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section, this method is on the basis of fine and close oil field field development experiments Yield Influence Factors are analyzed, it proposes with the variation of oil reservoir transverse direction coefficient of heterogeneity reflection horizontal segment transverse direction oiliness, the horizontal segment obtained with well logging reflects the size of oiliness along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area, with the variation of well log interpretation permeability reflection reservoir permeability, to log well brittleness index and man-made fracture enters ground liquid measure concentrated expression man-made fracture development degree, to realize the preferable prediction of the more cluster volume fracturing horizontal well productions of fine and close oil section, realizing reduces investment risk in fine and close oily scale development, improve the target for producing and building benefit.

Description

A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section
Technical field
The invention belongs to oil field development technical fields, and in particular to a kind of more cluster volume fracturing horizontal wells of densification oil section produce Measure prediction technique.
Background technique
Fine and close oil, which refers to, to be clipped in or close in the compact reservoir of high quality source rock series of strata, without extensive long-distance migration And the oil-gas accumulation formed, generally for pressure break without natural production capacity, the more cluster volume fracturings of horizontal well in segments, which are developed, at present does not have become cause The main means of close oil exploitation;Fine and close oil level well development and the in the past most significant difference of low-permeability oil deposit horizontal well development are single Well investment greatly and builds that produce the period longer, to reduce investment risk in fine and close oily scale development, reaches the target for improving and producing and building benefit, It is segmented the hot issue that more cluster volume fracturing horizontal well production predictions have become fine and close oil exploitation, while being also that a difficult point is asked Topic is mainly reflected in following 2 aspects.
1, fine and close oily reservoir transverse direction oiliness changes greatly, and the variation of horizontal well production and lateral oiliness has close pass System, existing Horizontal Well Log Interpretation model and test method are difficult to reflect the variation of lateral oiliness heterogeneity.This is Because it is radially not symmetrical that horizontal well is different from straight well, the closely horizontal penetrating ground of horizontal well, and the medium of wellbore, while by The influence of gravity factor, instrument well logging state is usually bias, and bias has in various degree the measurement of various loggers Influence, most notable one is the correlation of well log interpretation oil saturation and yield in the comparable situation of transformation scale It is poor, need to screen the influence factor sensitive to yield.
2, compact reservoir rock brittleness index is larger, and reservoir reconstruction is larger, and the fracture network of formation is more complicated, retouches The technology for stating pressure-break length, width and height that artificial seam is netted is also immature, currently used man-made fracture detection technique -- The result of underground micro-seismic monitoring method test is only microseism signal parameter, cannot represent true fracture pattern.
From the point of view of literature survey pressure break horizontal well production prediction method situation, existing prediction technique can be summarized as two classes: one Class is method for numerical simulation, and another kind of is economics analysis model prediction method.However whether method for numerical simulation, or theory Analytic modell analytical model prediction technique, when carrying out production forecast, due to the more cluster volume fracturing horizontal well man-made fracture ginsengs of fine and close oil section Number description technique is also immature, and the well log interpretation oil saturation that there is routine cannot reflect horizontal well transverse direction oiliness The problem of variation, causes existing method precision in filed application poor.It needs to be segmented more cluster bodies from the fine and close grease horizontal well of influence Three oiliness for splitting yield, permeability and development degree of micro cracks in oil aspects are overstock, screening becomes with fine and close grease horizontal well actual production Change sensitive parameter.
Summary of the invention
The purpose of the present invention is overcome method for numerical simulation and economics analysis method to be difficult to preferably reflect that fine and close oily reservoir is horizontal The problem difficult with the description of man-made fracture development degree is changed greatly to oiliness.
For this purpose, the present invention provides a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section, including with Lower step:
After step 1) horizontal well drilling, oil reservoir transverse direction coefficient of heterogeneity HE is obtainedf
Step 2), along the permeability of journey oil reservoir, obtains horizontal segment and permeates along the well logging of journey oil reservoir according to horizontal segment in well logging result Rate enveloping surface area K';
Step 3) is according to when well logging as a result, be eliminated bores in real time during horizontal well drilling and entrance mud flow rate Standard total hydrocarbon in gas logging value QT, net horizontal section is obtained along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area Q using definite integralT';
Step 4) Barnett shale brittleness index formula, passes through compressional wave time difference, shear wave slowness and rock volume density value Calculate rock brittleness index;
It is crisp along journey oil reservoir to obtain horizontal segment using definite integral principle according to the rock brittleness index being calculated for step 5) Sex index enveloping surface area B I';
Step 6) enters the cumulative read group total individual well of ground liquid measure according to every section during the more cluster volume fracturings of segmentation and always enters ground liquid Measure Lv
Step 7) obtains being segmented more cluster volume fracturing horizontal well production Q predictor formulas:
Q=1.628*Ln (HEf×K'×QT'×BI'×LV)-50.717。
Step 1) the oil reservoir transverse direction coefficient of heterogeneity HEfHorizontal segment oil reservoir total length L is met to boreoWith discontinuous oil layer section The ratio of number N:
In formula, HEfFor oil reservoir transverse direction coefficient of heterogeneity, m/ sections;LoHorizontal segment oil reservoir total length, m are met to bore;N is to bore to meet water Oil layer section number, a in flat section;LiI-th of oil reservoir segment length in horizontal segment, m are met to bore.
Step 2) horizontal segment is calculate by the following formula to obtain along journey oil reservoir well logging permeability enveloping surface area K':
Wherein, K' is horizontal segment along journey oil reservoir well logging permeability enveloping surface area, mDm;
kijTo bore the permeability met in horizontal segment in i-th of oil layer section at j-th of sampled point, mD;
Δ l is well logging sampling interval, m.
Step 3) net horizontal section is along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area QT' it is calculate by the following formula to obtain:
Wherein, QT' it is horizontal segment along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area, %m;QTijTo bore the level of chance Corresponding standard total hydrocarbon in gas logging value at i-th of oil layer section, j-th of sampled point, % in section;
Step 4) rock brittleness index is calculate by the following formula to obtain:
Wherein,
In formula, BIijFor corresponding well logging brittleness index at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, %; ΔEijFor Young's modulus after corresponding normalization at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, dimensionless;Δμij To bore the Poisson's ratio met in horizontal segment at i-th of oil layer section, j-th of sampled point after corresponding normalization, dimensionless;EijIt is met to bore Corresponding Young's modulus at i-th of oil layer section, j-th of sampled point in horizontal segment, 104MPa;μijI-th of oil in horizontal segment is met to bore Corresponding Poisson's ratio at j-th of sampled point of interval, dimensionless;ρbijI-th of oil layer section, j-th of sampled point in horizontal segment is met to bore Locate corresponding rock volume density, g/cm3;ΔtsijIt is corresponding at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment The shear wave slowness of rock, μ s/m;ΔtpijThe vertical of corresponding rock at i-th of oil layer section, j-th of sampled point is met in horizontal segment to bore The wave time difference, μ s/m.
Step 5) horizontal segment is obtained along journey oil reservoir brittleness index enveloping surface area B I' by following formula:
Individual well described in step 6) always enters ground liquid measureWherein, LvAlways enter ground liquid measure, m for individual well3;Lvi Enter ground liquid measure, m to be segmented more i-th sections of cluster volume fracturing3
The standard total hydrocarbon in gas logging value QTWell logging real-time during horizontal well drilling is obtained by antitrigonometric function method Total hydrocarbon in gas logging value qtIt is corrected to obtain:
In formula, νijFor actual well drilled flow quantity at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, m3/min;tij When being bored for reality at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, min/m;νoFor block standard well liquid entrance, m3/min;toWhen being bored for block standard, min/m;qtijIt is corresponding at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment With brill total hydrocarbon in gas logging value, %.
The shear wave slowness Δ t of the rocksijCalculating formula for log well when only to compressional wave time difference Δ tpijIt is tested, is not had There is the case where test shear wave slowness.
The beneficial effects of the present invention are: this method provided by the invention fine and close oil field field development experiments yield effect because On the basis of element analysis, propose to obtain with the variation of oil reservoir transverse direction coefficient of heterogeneity reflection horizontal segment transverse direction oiliness with well logging Horizontal segment along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area reflection oiliness size, with well log interpretation permeability reflection The variation of reservoir permeability, to log well brittleness index and man-made fracture enters ground liquid measure concentrated expression man-made fracture development degree, from And realize the preferable prediction of the more cluster volume fracturing horizontal well productions of fine and close oil section, it realizes to reduce and be invested in fine and close oily scale development Risk improves the target for producing and building benefit.
It is described in further details below in conjunction with attached drawing.
Detailed description of the invention
Fig. 1 is oil reservoir transverse direction coefficient of heterogeneity HEfWith the relation curve of the horizontal well individual well daily output;
Fig. 2 is the relation curve of mean permeability k and the horizontal well individual well daily output at individual well crack;
Fig. 3 is average well logging porosity at individual well crackWith the relation curve of the horizontal well individual well daily output;
Average well-log oil saturation S at Fig. 4 individual well crackoWith the relation curve of the horizontal well individual well daily output;
The relation curve of average rock brittleness index BI and the horizontal well individual well daily output at Fig. 5 individual well crack;
Average total hydrocarbon in gas logging value Q at the crack Fig. 6TWith the relation curve of the horizontal well individual well daily output;
Fig. 7 is the relation curve of well logging permeability enveloping surface area K' and the horizontal well individual well daily output;
Fig. 8 is the relation curve of well logging porosity enveloping surface area Φ ' Yu the horizontal well individual well daily output;
Fig. 9 is well-log oil saturation enveloping surface area So' with the relation curve of the horizontal well individual well daily output;
Figure 10 is the relation curve of well logging brittleness index enveloping surface area B I' and the horizontal well individual well daily output;
Figure 11 is standard total hydrocarbon in gas logging value enveloping surface area QT' with the relation curve of the horizontal well individual well daily output;
Figure 12 well is segmented more cluster volume fracturings and enters ground liquid measure LvWith the relation curve of the horizontal well individual well daily output;
Figure 13 well is segmented the relation curve of more cluster volume fracturing seam number of segment STA and the horizontal well individual well daily output;
Figure 14 is that individual well is segmented more cluster volume fracturings and is averaged the relation curve of sand feeding amount SAN and the horizontal well individual well daily output;
Figure 15 is the relation curve that individual well is segmented more cluster volume fracturing average discharge PR Yu the horizontal well individual well daily output;
Figure 16 is that individual well is segmented more cluster volume fracturings and is averaged the relation curve of sand ratio PC and the horizontal well individual well daily output;
Figure 17 is the relation curve of enveloping surface coefficient Yu the horizontal well individual well daily output;
Figure 18 is that GP47-64 borehole logging tool explains individual well card.
Specific embodiment
Embodiment 1:
Present embodiments provide a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section, including following step It is rapid:
After step 1) horizontal well drilling, oil reservoir transverse direction coefficient of heterogeneity HE is obtainedf
Step 2), along the permeability of journey oil reservoir, obtains horizontal segment and permeates along the well logging of journey oil reservoir according to horizontal segment in well logging result Rate enveloping surface area K';
Step 3) is according to when well logging as a result, be eliminated bores in real time during horizontal well drilling and entrance mud flow rate Standard total hydrocarbon in gas logging value QT, net horizontal section is obtained along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area Q using definite integralT';
Step 4) Barnett shale brittleness index formula, passes through compressional wave time difference, shear wave slowness and rock volume density value Calculate rock brittleness index;
It is crisp along journey oil reservoir to obtain horizontal segment using definite integral principle according to the rock brittleness index being calculated for step 5) Sex index enveloping surface area B I';
Step 6) enters the cumulative read group total individual well of ground liquid measure according to every section during the more cluster volume fracturings of segmentation and always enters ground liquid Measure Lv
Step 7) obtains being segmented more cluster volume fracturing horizontal well production Q predictor formulas:
Q=1.628*Ln (HEf×K'×QT'×BI'×LV)-50.717。
The horizontal segment that the present invention is obtained with well logging is along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area reflection oiliness Size, with the variation of well log interpretation permeability reflection reservoir permeability, with log well brittleness index and man-made fracture to enter ground liquid measure comprehensive Reflection man-made fracture development degree is closed, a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section are established in guidance, The advantage that there is this method parameter to be easy to get with high reliablity.
Embodiment 2:
(1) fine and close oil level well production sensitive parameter screening
Influencing the influence factor that fine and close grease horizontal well is segmented more cluster volume fracturing yield has geologic(al) factor and engineering factor.Ground Consider that reservoir oiliness, reservoir permeability and reservoir seam net form complexity in quality factor, wherein reservoir oiliness can be used 4 oil reservoir transverse direction coefficient of heterogeneity, well logging total hydrocarbon in gas logging value, well-log oil saturation, well logging porosity parameters are characterized, storage Layer permeability is characterized with well logging permeability, and reservoir seam net forms complexity and characterized with rock brittleness index;Engineering Factor mainly influences reservoir seam net development degree after volume fracturing transformation, mainly includes into ground liquid measure, artificial fracture transformation section Than 5 parameters of number, sand feeding amount, discharge capacity and sand;
Step 1: geologic(al) factor screening
(1) oil reservoir transverse direction coefficient of heterogeneity HEf: according to well log interpretation conclusion, counts every mouthful of sample level well horizontal segment and bore Meet oil reservoir length LoAnd horizontal segment oil layer section number N, obtain the oil reservoir transverse direction coefficient of heterogeneity HE of every mouthful of sample level wellf
(2) sample level well transverse direction coefficient of heterogeneity HE is calculated according to formula (1)f, do lateral coefficient of heterogeneity with it is corresponding The scatter plot of horizontal well production, as shown in Figure 1, the good relationship of regression formula and sample point, therefore oil reservoir is laterally non-equal Matter coefficient is as the main geologic parameter for influencing fine and close oil level well production factor;
Geologic parameter of the conventional horizontal well Analysis On Production-affecting Fact-ors at horizontal segment pressure-break represents entire horizontal The parameter of well, for huge discharge volume fracturing densification grease horizontal well, using same parameter statistic to fine and close grease horizontal well Influence factor is analyzed;
(3) averagely log well permeability k at individual well crack;
(4) average well logging porosity at individual well crack
(5) average well-log oil saturation S at individual well cracko
(6) average total hydrocarbon in gas logging value Q at individual well crackT
To the total hydrocarbon in gas logging value q that well logging obtains in real time during horizontal well drillingt, it is corrected using antitrigonometric function method Correction, is eliminated when boring and the standard total hydrocarbon in gas logging value Q of entrance mud flow rateT
Standard total hydrocarbon in gas logging value
(7) average rock brittleness index BI at individual well crack;
Rock brittleness index BI cannot be directly obtained by log, with Barnett shale brittleness index calculation formula Long 7 compact reservoir brittleness indexs are calculated according to compressional wave time difference, shear wave slowness and rock volume density value;
Brittleness index
Normalize Young's modulus
Normalize Poisson's ratio
Young's modulus
Poisson's ratio
It is calculated ground using the empirical equation of gas-free sandstone or argillaceous sandstone stratum for shear wave estimation is suitable for Layer shear wave slowness Δ ts
(8) the average geologic parameter at horizontal well crack is calculated according to formula (1)~(6), and does each geologic parameter and water The scatter plot of the horizontal well individual well daily output, as shown in Fig. 2~Fig. 6, the various regions it can be seen from 1 regressive trend line relative coefficient of table Average value at matter parameter crack and the correlation of yield are poor, therefore analyze and consider entire horizontal segment along journey reservoir heterogeneity Geologic parameter enveloping surface area and yield relationship;
(9) after according to horizontal well drilling, horizontal segment reservoir permeability in well log interpretation conclusion, using definite integral original Reason obtains horizontal segment along journey oil reservoir well logging permeability enveloping surface area K':
(10) after according to horizontal well drilling, horizontal segment oil reservoir porosity in well log interpretation conclusion, using definite integral original Reason, obtains horizontal segment along journey oil reservoir well logging porosity enveloping surface area Φ ':
(11) after according to horizontal well drilling, horizontal segment oil reservoir oil saturation in well log interpretation conclusion, using constant volume Divide principle, obtains horizontal segment along journey oil reservoir well-log oil saturation enveloping surface area So':
(12) to the total hydrocarbon in gas logging value q that well logging obtains in real time during horizontal well drillingt, carried out using antitrigonometric function method Correction correction, is eliminated when boring and the standard total hydrocarbon in gas logging value Q of entrance mud flow rateT, using definite integral principle, obtain water Flat section is along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area QT':
Standard total hydrocarbon in gas logging value
Horizontal segment is along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area:
(13) rock brittleness index BI cannot be directly obtained by log, be calculated with Barnett shale brittleness index Formula calculates long 7 compact reservoir brittleness indexs according to compressional wave time difference, shear wave slowness and rock volume density value;
Rock brittleness index
Normalize Young's modulus
Normalize Poisson's ratio
Young's modulus
Poisson's ratio
It is calculated ground using the empirical equation of gas-free sandstone or argillaceous sandstone stratum for shear wave estimation is suitable for Layer shear wave slowness Δ ts:
Horizontal segment is obtained along journey oil reservoir well logging index using definite integral principle according to the rock brittleness index being calculated Enveloping surface area B I';
(14) logging program sampling interval used in Changqing oilfields is 0.125m, i.e. Δ l=0.125m, therefore formula (7)~(11) can simplify into following form:
(15) each sample level well geologic parameter horizontal segment is calculated along journey oil reservoir enveloping surface according to formula (12)~(16) Area does the scatter plot (Fig. 7~Figure 13) of these parameters Yu the individual well daily output.The correlation of Trendline is obtained according to regression formula Coefficients R2(being shown in Table 1), it can be seen that compared to the relationship of average value at crack and the individual well daily output, each geologic parameter enveloping surface face Product is more preferable with the relationship of the individual well daily output.Oil reservoir well logging the permeability enveloping surface area, standard of good relationship are filtered out simultaneously Total hydrocarbon in gas logging value enveloping surface area and brittleness index enveloping surface area are as the principal element for influencing fine and close oil level well production.
Step 2: engineering factor screening
Engineering factor mainly influences reservoir seam net development degree after volume fracturing transformation, mainly includes into ground liquid measure, manually Than 5 parameters of pressure-break number of segment, sand feeding amount, discharge capacity and sand;
(16) the more cluster volume fracturings of individual well segmentation enter ground liquid measure Lv
(17) individual well is segmented more cluster volume fracturings and stitches number of segment STA;
STA=n (18)
(18) individual well is segmented more cluster volume fracturings and is averaged sand feeding amount SAN;
(19) individual well is segmented more cluster volume fracturing average discharge PR;
(20) individual well is segmented more cluster volume fracturings and is averaged sand ratio PC;
According to each sample horizontal well Single well project parameter that formula (17)~(21) calculate, each engineering parameter and individual well day are done The scatter plot (Figure 12~Figure 16) of yield, according to the size (table 1) of relative coefficient, preferably individual well enters ground liquid measure and causes as influence The principal element of close oil level well production;
(2) fine and close oil level well production formulary regression
Each influence factor and the relationship of the individual well daily output are analyzed, as shown in figure 17,5 parametric regressions obtain densification The more cluster volume fracturing horizontal well production predictor formulas of oil section;
Q=1.628*Ln (HEf×K'×QT'×BI'×LV)-50.717 (22)
Q is volume fracturing horizontal well production, t/d.
The related coefficient of table 1 fine and close oil level well production influence factor and yield scatter plot
Embodiment 3:
Heshui long 7 is controlled by the more material resources in western, southwest and south, based on the material resource of the west and south, develops delta and lake Two kinds of type of sedimentary facies;Major developmental delta front slump is formed by turbidite Reservoir Body.Turbidity channel sand is as the area Skeleton matching is distributed in shape, lumps, and sand thickness is big, and oil-layer distribution is relatively stable, and thickness is larger, and oil reservoir has larger Scale, resource potential are big.
GP47-64 is the long 7 oil reservoir development horizontal wells (Figure 18) of Heshui, and horizontal section length 680m is bored and met oil layer section 647m bores and meets oil layer section number 7, adds sand volume fracturing reforming mode using water-jet annular space, enters ground liquid measure 3550m3, oil Interval logs well permeability enveloping surface area as 143.8mDm, and total hydrocarbon in gas logging value enveloping surface area is 19137.1%m, brittleness Exponential envelope face area is 34938.2%m, and oil reservoir transverse direction coefficient of heterogeneity is 96.3m/ sections.It is produced according to fine and close grease horizontal well Predictor formula is measured, GP47-64 well individual well is calculated and has a daily output of 11.1t/d, practical individual well has a daily output of 10.5t/d, predicts error It is 5.9%, effect is preferable, and specific calculating process is shown in GP47-64 production forecast process.
GP47-64 production forecast process:
Step 1: oil reservoir transverse direction coefficient of heterogeneity HE is calculatedf:
Step 2: horizontal segment is calculated along journey oil reservoir and logs well permeability enveloping surface area (being shown in Table 2):
2 horizontal segment of table is along journey oil reservoir well logging permeability enveloping surface area calculation step
Step 3: horizontal segment is calculated along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area (being shown in Table 3):
3 horizontal segment of table is along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area calculation step
Step 4: horizontal segment is calculated along journey oil reservoir and logs well brittleness index enveloping surface area (being shown in Table 4):
Table 4 is along journey oil reservoir brittleness index enveloping surface area calculation step
Step 5: the ground liquid measure calculating individual well that enters according to every section during the more cluster volume fracturings of segmentation always enters ground liquid measure Lv:
Step 6: GP47-64 yield is calculated:
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
GP47-64 actual production is 10.5t/d, and calculated value and actual value error are 5.9%.
The foregoing examples are only illustrative of the present invention, does not constitute the limitation to protection scope of the present invention, all It is within being all belonged to the scope of protection of the present invention with the same or similar design of the present invention.

Claims (9)

1. a kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section, which comprises the following steps:
After step 1) horizontal well drilling, oil reservoir transverse direction coefficient of heterogeneity HE is obtainedf
Step 2), along the permeability of journey oil reservoir, obtains horizontal segment along journey oil reservoir well logging permeability packet according to horizontal segment in well logging result Network face area K';
Step 3) is according to when well logging as a result, be eliminated bores in real time during horizontal well drilling and the standard of entrance mud flow rate Total hydrocarbon in gas logging value QT, net horizontal section is obtained along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area Q using definite integralT';
Step 4) Barnett shale brittleness index formula is calculated by compressional wave time difference, shear wave slowness and rock volume density value Rock brittleness index;
Step 5) obtains horizontal segment and refers to along journey oil reservoir brittleness according to the rock brittleness index being calculated using definite integral principle Number enveloping surface area B I';
Step 6) enters the cumulative read group total individual well of ground liquid measure according to every section during the more cluster volume fracturings of segmentation and always enters ground liquid measure Lv
Step 7) obtains being segmented more cluster volume fracturing horizontal well production Q predictor formulas:
Q=1.628*Ln (HEf×K'×QT'×BI'×LV)-50.717。
2. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 1, feature It is: step 1) the oil reservoir transverse direction coefficient of heterogeneity HEfHorizontal segment oil reservoir total length L is met to boreoWith discontinuous oil layer section number The ratio of N:
In formula, HEfFor oil reservoir transverse direction coefficient of heterogeneity, m/ sections;LoHorizontal segment oil reservoir total length, m are met to bore;N is discontinuous oil reservoir Section number, it is a;LiI-th of oil reservoir segment length in horizontal segment, m are met to bore.
3. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 1, feature Be: step 2) horizontal segment is calculate by the following formula to obtain along journey oil reservoir well logging permeability enveloping surface area K':
Wherein, K' is horizontal segment along journey oil reservoir well logging permeability enveloping surface area, mDm;
N is discontinuous oil layer section number, a;kijTo bore the infiltration met in horizontal segment in i-th of oil layer section at j-th of sampled point Rate, mD;Δ l is well logging sampling interval, m.
4. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 1, feature Be: step 3) net horizontal section is along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area QT' it is calculate by the following formula to obtain:
Wherein, QT' it is horizontal segment along journey oil reservoir standard total hydrocarbon in gas logging value enveloping surface area, %m;N is discontinuous oil layer section Number, it is a;QTijFor corresponding standard total hydrocarbon in gas logging value at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, %;Δ l is Well logging sampling interval, m;vijFor actual well drilled flow quantity at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, m3/min; tijWhen being bored for reality at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, min/m;voEnter for block standard well liquid Mouthful, m3/min;toWhen being bored for block standard, min/m;qtijIt is corresponded at i-th of oil layer section, j-th of sampled point to bore to meet in horizontal segment With bore total hydrocarbon in gas logging value, %.
5. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 1, feature Be: step 4) rock brittleness index is calculate by the following formula to obtain:
Wherein,
In formula, BIijFor corresponding well logging brittleness index at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, %;ΔEij It bores and meets in horizontal segment at i-th of oil layer section, j-th of sampled point Young's modulus, dimensionless after corresponding normalization;ΔμijIt is met to bore Poisson's ratio in horizontal segment at i-th of oil layer section, j-th of sampled point after corresponding normalization, dimensionless;EijIt bores and meets in horizontal segment Corresponding Young's modulus at i-th of oil layer section, j-th of sampled point, 104MPa;μijI-th of oil layer section jth in horizontal segment is met to bore Corresponding Poisson's ratio, dimensionless at a sampled point;ρbijIt is corresponding at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment Rock volume density, g/cm3;ΔtsijTo bore the cross for meeting corresponding rock at i-th of oil layer section, j-th of sampled point in horizontal segment The wave time difference, μ s/m;To bore the compressional wave time difference for meeting corresponding rock at i-th of oil layer section, j-th of sampled point in horizontal segment, μ s/m。
6. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 1, feature Be: step 5) horizontal segment is obtained along journey oil reservoir brittleness index enveloping surface area B I' by following formula:
Wherein, N is discontinuous oil layer section number, a;BIijIt is corresponded at i-th of oil layer section, j-th of sampled point to bore to meet in horizontal segment Well logging brittleness index, %;Δ l is well logging sampling interval, m.
7. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 1, feature Be: individual well described in step 6) always enters ground liquid measureWherein, LvAlways enter ground liquid measure, m for individual well3;LviFor It is segmented i-th section of more cluster volume fracturings and enters ground liquid measure, m3
8. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 4, feature It is, the standard total hydrocarbon in gas logging value QTThe gas that well logging obtains in real time during horizontal well drilling is surveyed by antitrigonometric function method Total hydrocarbon value qtIt is corrected to obtain:
In formula, νijFor actual well drilled flow quantity at i-th of oil layer section, j-th of sampled point in brill chance horizontal segment, m3/min;tijTo bore In chance horizontal segment at i-th of oil layer section, j-th of sampled point when practical brill, min/m;νoFor block standard well liquid entrance, m3/ min;toWhen being bored for block standard, min/m;qtijFor bore meet in horizontal segment at i-th of oil layer section, j-th of sampled point it is corresponding with Bore total hydrocarbon in gas logging value, %.
9. a kind of more cluster volume fracturing horizontal well production prediction techniques of fine and close oil section according to claim 5, feature It is: the shear wave slowness Δ t of the rocksijCalculating formula for log well when only to compressional wave time differenceIt is tested, is not surveyed The case where trying shear wave slowness.
CN201610258620.4A 2016-04-22 2016-04-22 A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section Active CN105931125B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610258620.4A CN105931125B (en) 2016-04-22 2016-04-22 A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610258620.4A CN105931125B (en) 2016-04-22 2016-04-22 A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section

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 A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section

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 single well yield contribution rate of fracture and matrix to super-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 single well yield contribution rate of fracture and matrix to super-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) A kind of more cluster volume fracturing horizontal well production prediction techniques of densification oil section
CN109441422B (en) Shale gas well spacing optimization mining method
Gherabati et al. The impact of pressure and fluid property variation on well performance of liquid-rich Eagle Ford shale
CN106761677B (en) Logging prediction method for single-well productivity of shale gas horizontal well
CN103413030B (en) A kind of fracture-cavity type carbonate gas reservoir protection analysis method and system
CN106285646B (en) Drilling well loss horizon recognition methods based on multi-information fusion
CN106842301B (en) A kind of quantitative judge and prediction technique of tuffaceous sandstone Favorable Reservoir
CN102041995A (en) System for monitoring complicated oil deposit flooding conditions
CN103857876A (en) System and method for performing wellbore fracture operations
CN102707333A (en) Shale gas resource/reserve measurement method
Fang et al. Production prediction for fracture-vug carbonate reservoirs using electric imaging logging data
CN110043254A (en) A kind of acquisition methods based on cable formation testing data formation effective permeability
CN102621586B (en) Stratum data processing method for identifying stratum attribute
Matsumoto et al. In-situ permeability of fault zones estimated by hydraulic tests and continuous groundwater-pressure observations
Okeahialam et al. Completion optimization under constraints: An Eagle Ford shale case study
Xu et al. Fracability evaluation method for tight sandstone oil reservoirs
Zhou et al. Fracture prediction of tight sandstone reservoirs using outcrops and log curve-based extremum method: a case study of the Chang 7 member of the Yanchang Formation in block X, Ordos Basin
Avasthi et al. In-situ stress evaluation in the McElroy field, West Texas
Ortega et al. Quantitative properties from drill cuttings to improve the design of hydraulic-fracturing jobs in horizontal wells
Wallace et al. Understanding Completion Performance in Niobrara-Codell Reservoirs Through the Use of Innovative Software-Guided Workflows and Models
Ortega et al. Use of drill cuttings for improved design of hydraulic fracturing jobs in horizontal wells
Sabea et al. Geological model of the Khabour Reservoir for studying the gas condensate blockage effect on gas production, Akkas Gas Field, Western Iraq
Chacon et al. Effects of stress on fracture properties of naturally fractured reservoirs
Evans et al. A geological approach to permeability prediction in clastic reservoirs
CN109538199A (en) A kind of coal measure strata air content evaluation method, device and electronic equipment

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