CN104749622B - One kind is based on petrophysical mud shale compressibility quantitatively characterizing method - Google Patents
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Abstract
Petrophysical mud shale compressibility quantitatively characterizing method is based on the invention discloses one kind.Comprise the following steps：（1）Set up mud shale compressibility Mathematical Modeling；（2）Analysis formation parameter and mechanical relationship, preferably stratum mechanics parameter characterize the factor；（3）Recurrence fits compression strength elastic parameter and characterizes formula and set up formation fracture pressure elastic parameter sign formula, principal stress elastic parameter sign formula；（4）Compressibility index is set up to characterize formula and verify calculating compressibility index integrated data body；（5）Quantitatively characterizing stratum compressibility is simultaneously predicted.This method passes through multi parameter analysis, select the Efficient Characterization factor of mud shale stratum compressibility, build the sign formula of mud shale compressibility index, so as to realize the quantitatively characterizing of mud shale compressibility, that sets up mud shale compressibility sentences knowledge standard, the target of formation breakdown transformation interval is instructed simultaneously preferably, the cost of mud shale exploration is reduced, and effectively raises the success rate of mud shale exploration.
Description
Technical field
The stratum compressibility evaluation method field during geological prospecting is hidden the present invention relates to unconventionaloil pool, is particularly related to
And it is based on rock physicses, the quantitatively characterizing method of assay mud shale compressibility index to one kind.
Background technology
Stratum compressibility is to characterize the feasibility that stratum is deformed, is broken, destroying under external force.Stratum compressibility
Research evaluation has clear and definite directive significance for the validity that crustal stress is acted on, shelly ground prediction, the fracturing reform of reservoir.
At present, also the compressibility of mud shale stratum is predicted using geophysical information without scholar, SPE115258
Document《A Practial Use of Shale Petrophysics for Stimulation Design
Optimization:All Shale Plays Are Not Clone of the Barnett Shale》Using fragility experience
Formula asks for brittleness index, the approximate compressibility for reacting mud shale stratum.Oil drilling technology the 4th phase in 2012《Shale gas
Reservoir rock mechanical characteristic and brittleness evaluation》The method test mud shale mechanical characteristic of middle use laboratory test, but in reality
In exploration, brittle shale stratum high does not have good compressibility（Such as L69 wells）, possess compression strength higher on the contrary,
Explanation carries out fuzzy evaluation with brittleness index to the compressibility of mud shale stratum has greatly uncertainty.
According to the relation technological researching of the applicant, it is found that mud shale compressibility is close with principal stress, fracture pressure change
Correlation, the poor size of principal stress and fracture pressure react stratum can pressure break complexity, when general difference comparsion is big, can press
Property is poorer.The relation and rupture pressure of principal stress and elastic parameter are played in research by actual well drilled Information System research and establishment
Power and the relation of elastic parameter, establish the quantitatively characterizing formula of mud shale compressibility, are that the compressibility of mud shale stratum is quantified
Evaluate and provide a kind of geophysics quantitative identification method, realize the earthquake prediction of stratum compressibility.
The content of the invention
The purpose of the present invention is directed to the problem of prior art presence, there is provided one kind is applied to mud shale stratum, based on rock
The mud shale compressibility quantitatively characterizing method of stone physics.
The basic thought of discriminant analysis of the present invention is the difference by maximum stress and fracture pressure, and obtaining mud shale can press
The discrimination standard of sex index, maximum stress and fracture pressure are characterized with geophysical parameterses, are achieved in the earth of compressibility
Physics is predicted.
The purpose of the present invention is realized by following technical solution：
Based on petrophysical mud shale compressibility quantitatively characterizing method, by the sign factor of preferred stratum dynamics, knot
Close prestack parametric inversion and obtain mud shale compressibility integrated data body quantitatively characterizing stratum compressibility, comprise the following steps：
（1）Set up mud shale compressibility Mathematical Modeling；
（2）Analysis formation parameter and mechanical relationship, preferably stratum mechanics parameter characterize the factor；
（3）Recurrence fits compression strength elastic parameter and characterizes formula and set up formation fracture pressure elastic parameter sign public affairs
Formula, principal stress elastic parameter characterize formula；
（4）Compressibility index is set up to characterize formula and verify calculating compressibility index integrated data body；
（5）Quantitatively characterizing stratum compressibility is simultaneously predicted.
It is above-mentioned based on petrophysical mud shale compressibility quantitatively characterizing method, its prioritization scheme is：
（1）Use for reference the formation parameter data (P of fracture pressure empirical equation and known actual measurementp, u, Po, K), ask for well
Fracture pressure
In formula, Pf：Fracture pressure, Pp：Pore pressure, u：Poisson's ratio Po:Overburden pressure k：Compression strength；
By contrasting the numerical analysis of fracture pressure and maximum principal stress, porosity curve and experiment with reference to actual measurement
Room analysis result, sets up the basic mathematic model of mud shale compressibility, i.e.,
BI(Break)=ξ (σmax-Pf)+ε
（1）
In formula, BI(Break)：Compressibility index, σmax：Maximum stress, Pf：Formation fracture pressure, ε, ξ：Correction coefficient；
（2）Foundation and the relevant parameter information bank of mud shale stratum, physics parameter of the parameter information including mud shale,
Rock physicses elastic parameter, mineralogical composition evaluating, and test analysis are carried out to parameter information；Each observation ykVariation
Size, side value y is seen with this timekWith the n average value of observationDifferenceTo represent, and whole n sight
The total variance of measured value can be by total sum of squares of deviations
Wherein:Referred to as regression sum of square, is regressand valueWith averageDifference quadratic sum, it
Reflect independent variable x1,x2,x3,...,xmChange caused by y fluctuation；
Referred to as residual sum of square, is measured value ykWith regressand valueDifference quadratic sum, it be by
What test error and other factorses caused；
To check total regression effect, dimensionless index is used
R is referred to as multiple correlation coefficient；
（3）Multiple-factor is carried out respectively to principal stress, fracture pressure, compression strength as independent variable preferably to characterize the factor
Return, due to the number m of independent variable>1, defining regression formula is
Y=F（X1, X2…Xm）+ε （4）
Wherein XmIt is the number of explanatory variable, by carrying out multiple-factor recurrence point to principal stress, compression strength, fracture pressure
Analysis fitting, respectively obtains the fitting formula of principal stress, fracture pressure, compression strength.
Pf=-0.14×YME_STA+0.994×BMK_STA+2.77×SMG_STA+24.59（5）
σmax=-0.02×YME_STA+0.698×BMK_STA+0.459×SMG_STA+42.81（6）
K=-0.13×YME_STA+0.8×BMK_STA+2.78×SMG_STA-13.6（7）
In formula, Pf：Fracture pressure, σ max：Maximum principal stress, K：Compression strength, YME_STA:Young's modulus, BMK_STA：
Bulk modulus, SMG_STA：Modulus of shearing；
（4）By step（3）In regression result be updated to formula（1）In, the stratum that arrangement obtains meeting research work area can
The sign formula of pressure property：
BI(Break)=K1×YME_STA-K2×BMK_STA-K3×SMG_STA+C （8）
In formula, K1K2K3C:Compensation coefficient, K1=0.12,K2=0.296,K3=2.311, C=18.22, YME_STA:Young mould
Amount, BMK_STA：Bulk modulus, SMG_STA：Modulus of shearing；
（5）With prestack inversion as technological means, Young's modulus data volume, bulk modulus data volume and the shearing of the whole district are obtained
Moduli data body, is calculated by data volume and sets up mud shale compressibility index integrated data model, realizes its compressibility index
Quantitatively characterizing, the compressibility to mud shale stratum is effectively predicted.
Such scheme is further included：
Step（2）The preferred interval transit time of physics parameter of middle mud shale, density；The preferred Young of rock physicses elastic parameter
Modulus, modulus of shearing and bulk modulus；The preferred brittle mineral content of mineralogical composition evaluating.
It is preferred that the preferred R of multiple correlation coefficient>0.9 formation parameter characterizes the factor as effective.
It is preferred that BI(Break)The area of ＞ 0 is optimal fracture zone, realizes the quantitatively characterizing of compressibility index and predicts.
Beneficial effects of the present invention：
The present invention is to be based on petrophysical mud shale compressibility index quantitatively characterizing method, it is contemplated that mud shale stratum is not
With the influence of mineral constituent, test analysis are carried out to petrophysical parameters such as principal stress, fracture pressure, compression strength, preferably had
Effect characterizes the factor and is accurately asked for, and has invented the quantitatively characterizing formula of mud shale compressibility index.The method achieve mud page
The quantitative forecast of rock compressibility, improves it and describes precision, is that the target of mud shale stratum fracturing reform interval is preferably provided
Foundation, with good application effect and promotion prospect.
Brief description of the drawings：
Accompanying drawing 1：Mud shale compressibility quantitatively characterizing method techniqueflow chart
Accompanying drawing 2：Maximum principal stress-fracture pressure and reservoir compressibility explanation figure
Accompanying drawing 3：Actual probing mud shale L69 well reservoir parameters curve maps
Accompanying drawing 4：Fracture pressure regression fit analysis and formula
Accompanying drawing 5：Maximum principal stress regression fit analysis and formula
Accompanying drawing 6：Compression strength regression fit analysis and formula
Accompanying drawing 7：L69 well compressibility parameter evaluation figures
Accompanying drawing 8：Y186 well compressibility index assessment figures
Accompanying drawing 9：The compressibility prediction plan of ES3_13 layers of BN areas group mud shale stratum
Specific embodiment：
Below in conjunction with accompanying drawing 1-9, the invention will be further described.
Step 1, the formation parameter data (P for using for reference fracture pressure empirical equation and known actual measurementp, u, Po, K), ask for
The fracture pressure of well
Pf：Fracture pressure Pp：Pore pressure
u：Poisson's ratio Po:Overburden pressure k：Compression strength
By contrasting the numerical analysis of fracture pressure and maximum principal stress, porosity curve and experiment with reference to actual measurement
Room analysis result, it can be seen that when maximum principal stress is more than fracture pressure, crack produces, and reservoir porosity preferably, is defined as
One class reservoir；Though porosity is poor, but still it is the good stratum of compressibility when maximum principal stress and fracture pressure approximately equal,
Reservoir properties can be improved through row by the fracturing technique in later stage, be defined as two class reservoirs；When fracture pressure is main much larger than maximum
During stress, the poor compressibility on stratum is defined as three class reservoirs（Such as Fig. 2）.Analyzed according to more than, set up the basic of stratum compressibility
Computation model, i.e.,
BI(Break)=ξ (σmax-Pf)+ε
（1）
BI(Break)：Compressibility index；σmax：Maximum stress；Pf：Formation fracture pressure；ε、ξ：Correction coefficient
The relevant parameter information bank of step 2, foundation and mud shale stratum, the parameter information mainly includes the physics of mud shale
Learn parameter such as interval transit time, density；Rock physicses elastic parameter such as Young's modulus, modulus of shearing, bulk modulus；Mineralogical composition is commented
Valency parameter, such as brittle mineral content, and test analysis are carried out to parameter information（Such as Fig. 3）.Each observation ykVariation size,
Conventional this time sight side value ykWith the n average value of observationDifference(referred to as deviation) is represented, and complete
The total variance of the observation of portion n times can be by total sum of squares of deviations
Wherein:Referred to as regression sum of square, is regressand valueWith averageDifference quadratic sum, it
Reflect independent variable x1,x2,x3,...,xmChange caused by y fluctuation.
Referred to as residual sum of square (or residual sum of squares (RSS)), is measured value ykWith regressand valueDifference
Quadratic sum, it is caused by test error and other factorses.
To check total regression effect, dimensionless index is often quoted
R is referred to as multiple correlation coefficient.Because regression sum of square U is actually the " side for reflecting whole independents variable in regression equation
Difference contribution ", therefore R2Be exactly the ratio shared in total regression quadratic sum of this contribution, thus R represent whole independents variable and because
The degree of correlation of variable y.Obvious 0≤R≤1.Multiple correlation coefficient is closer to 1, and regression effect is better, therefore it can be as inspection
Test an index of total regression effect.
Parameter information and principal stress, compression strength, the multiple correlation coefficient significance test of fracture pressure to well, it is preferably multiple
Coefficient correlation characterizes the factor more than 0.9 parameter as effective.By thinking, Young's modulus, modulus of shearing, volume mould
Amount is to rock mechanics parameters（Principal stress, fracture pressure, compression strength）With preferable correlation, preferably as mechanics parameter
Characterize the factor.
Step 3, using preferably characterize the factor principal stress, fracture pressure, compression strength are carried out respectively as independent variable it is many
Factorial regression, due to the number m of independent variable>1, defining regression formula is
Y=F（X1, X2…Xm）+ε （4）
Wherein XmIt is the number of explanatory variable, what the recurrence was associated with Multiple factors, by the optimal set of multiple independents variable
Amount to together to predict or estimate dependent variable, it is more more effective than being only predicted with an independent variable or being estimated, more meet reality.Pass through
Multiple-factor regression analysis fitting is carried out to principal stress, compression strength, fracture pressure（Fig. 4,5,6）, respectively obtain principal stress, rupture
The fitting formula of pressure, compression strength.
Pf=-0.14×YME_STA+0.994×BMK_STA+2.77×SMG_STA+24.59（5）
σmax=-0.02×YME_STA+0.698×BMK_STA+0.459×SMG_STA+42.81（6）
K=-0.13×YME_STA+0.8×BMK_STA+2.78×SMG_STA-13.6（7）
Pf：Fracture pressure σ max：Maximum principal stress K：Compression strength
YME_STA:Young's modulus BMK_STA：Bulk modulus SMG_STA：Modulus of shearing
Step 4, the regression result in step 3 is updated to formula（1）In, arrangement obtains meeting the stratum in research work area
The sign formula of compressibility：
Formula is as follows：
BI(Break)=K1×YME_STA-K2×BMK_STA-K3×SMG_STA+C （8）
K1K2K3C:Compensation coefficient,
K1=0.12,K2=0.296,K3=2.311,C=18.22
YME_STA:Young's modulus BMK_STA：Bulk modulus SMG_STA：Shearing
Modulus
The parameter has preferably reaction to stratum compressibility, as shown in fig. 7, L69 wells are in 2990m-3010m and 3040m-
Two sections of BI of 3070m（break）More than 0 value, reservoir fissure development, porosity is 5%, is the favourable interval of fracturing reform.2950m-
2980m, BI（break）0 value is similar to, though intrinsic fracture agensis, with fracturing reform.3070m-3090m, BI（break）
<- 30MPa, unsuitable fracturing reform.
Using the work area, other many cause for gossip well datas are verified to the formula, the parameter with reality analysis result compared with
It is be consistent (such as Fig. 8).
Step 5, with prestack inversion as technological means, obtain the Young's modulus data volume of the whole district, bulk modulus data volume is cut
Shear modulu data volume；With formula（8）The sign formula of stratum compressibility is computational methods, is calculated by data volume and sets up mud shale
Compressibility index integrated data model, realizes the quantitatively characterizing of its compressibility index, and the compressibility to mud shale stratum has
Effect prediction (such as Fig. 9).
Claims (4)
1. be based on petrophysical mud shale compressibility quantitatively characterizing method, it is characterized in that by the sign of preferred stratum dynamics because
Son, mud shale compressibility integrated data body quantitatively characterizing stratum compressibility is obtained with reference to prestack parametric inversion, is comprised the following steps：
(1) mud shale compressibility Mathematical Modeling is set up：
Use for reference the formation parameter data (P of fracture pressure empirical equation and known actual measurementp, u, Po, K), ask for the fracture pressure of well
In formula, Pf：Fracture pressure, Pp：Pore pressure, u：Poisson's ratio, Po:Overburden pressure, k：Compression strength；
By contrasting the numerical analysis of fracture pressure and maximum principal stress, porosity curve and laboratory point with reference to actual measurement
Analysis result, sets up the basic mathematic model of mud shale compressibility, i.e.,
BI(Break)=ξ (σmax-Pf)+ε (1)
In formula, BI(Break)：Compressibility index, σmax：Maximum stress, Pf：Formation fracture pressure, ε, ξ：Correction coefficient；
(2) formation parameter and mechanical relationship are analyzed, preferably stratum mechanics parameter characterizes the factor：
The relevant parameter information bank with mud shale stratum is set up, the parameter information includes physics parameter, the rock thing of mud shale
Reason elastic parameter, mineralogical composition evaluating, and test analysis are carried out to parameter information；Each observation ykVariation size,
Side value y is seen with this timekWith the n average value of observationDifferenceTo represent, and whole n observation is total
Variation can be by total sum of squares of deviations
Wherein:Referred to as regression sum of square, is regressand valueWith averageDifference quadratic sum, it reflect from
Variable x1,x2,x3,...,xmChange caused by y fluctuation；
Referred to as residual sum of square, is measured value ykWith regressand valueDifference quadratic sum, it be by experiment miss
What difference and other factorses caused；
To check total regression effect, dimensionless index is used
R is referred to as multiple correlation coefficient；
(3) return to fit compression strength elastic parameter sign formula and set up formation fracture pressure elastic parameter and characterize formula, master
Stress elastic parameter characterizes formula：
Multiple-factor recurrence is carried out respectively to principal stress, fracture pressure, compression strength as independent variable preferably to characterize the factor, by
In the number m of independent variable>1, defining regression formula is
Y=F (X1, X2…Xm)+ε (4)
Wherein XmIt is the number of explanatory variable, multiple-factor regression analysis plan is carried out by principal stress, compression strength, fracture pressure
Close, respectively obtain the fitting formula of principal stress, fracture pressure, compression strength,
Pf=-0.14 × YME_STA+0.994 × BMK_STA+2.77 × SMG_STA+24.59 (5)
σ max=-0.02 × YME_STA+0.698 × BMK_STA+0.459 × SMG_STA+42.81 (6)
K=-0.13 × YME_STA+0.8 × BMK_STA+2.78 × SMG_STA-13.6 (7)
In formula, Pf：Fracture pressure, σ max：Maximum principal stress, K：Compression strength, YME_STA:Young's modulus, BMK_STA：Volume
Modulus, SMG_STA：Modulus of shearing；
(4) compressibility index is set up to characterize formula and verify calculating compressibility index integrated data body：
Regression result in step (3) is updated in formula (1), arrangement obtains the table of the stratum compressibility for meeting research work area
Levy formula：
BI(Break)=K1×YME_STA-K2×BMK_STA-K3×SMG_STA+C (8)
In formula, K1、K2、K3、C:Compensation coefficient, K1=0.12, K2=0.296, K3=2.311, C=18.22, YME_STA:Poplar
Family name's modulus, BMK_STA：Bulk modulus, SMG_STA：Modulus of shearing；
(5) quantitatively characterizing stratum compressibility and predict：
With prestack inversion as technological means, Young's modulus data volume, bulk modulus data volume and the modulus of shearing number of the whole district are obtained
According to body, calculated by data volume and set up mud shale compressibility index integrated data model, realize the quantitative table of its compressibility index
Levy, the compressibility to mud shale stratum is effectively predicted.
2. petrophysical mud shale compressibility quantitatively characterizing method is based on according to claim 1, it is characterized in that mud in step (2)
The preferred interval transit time of physics parameter of shale, density；The preferred Young's modulus of rock physicses elastic parameter, modulus of shearing and volume
Modulus；The preferred brittle mineral content of mineralogical composition evaluating.
3. petrophysical mud shale compressibility quantitatively characterizing method is based on according to claim 1 or 2, it is characterized in that it is preferred that complex phase
The preferred R of relation number>0.9 formation parameter characterizes the factor as effective.
4. petrophysical mud shale compressibility quantitatively characterizing method is based on according to claim 3, it is characterized in that it is preferred that BI(Break)〉
0 area is optimal fracture zone, realizes the quantitatively characterizing of compressibility index and predicts.
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| CN104775810B (en) * | 2015-03-03 | 2016-05-18 | 西南石油大学 | A kind of shale gas reservoir compressibility evaluation method |
| CN106337682A (en) * | 2015-07-06 | 2017-01-18 | 中国石油化工股份有限公司 | Shale reservoir brittleness evaluating method |
| CN105046006B (en) * | 2015-07-29 | 2018-05-04 | 中国石油天然气股份有限公司 | A kind of shale gas reservoir horizontal well multistage productivity of fractured Forecasting Methodology and device |
| CN105426645B (en) * | 2016-01-12 | 2019-04-26 | 中国石油化工股份有限公司胜利油田分公司勘探开发研究院 | A kind of automatic control methods in the stratum ASC and system |
| CN106127343A (en) * | 2016-06-27 | 2016-11-16 | 成都理工大学 | A kind of analysis method of Formation overpressure origin mechanism |
| CN106372325A (en) * | 2016-08-31 | 2017-02-01 | 西南石油大学 | Method and device for obtaining elastic-plastic formationcircum-well stress field |
| CN107884261A (en) * | 2016-09-29 | 2018-04-06 | 中国石油化工股份有限公司 | A kind of strength sensitive evaluation method of shale reservoir |
| CN109209356B (en) * | 2017-07-06 | 2021-08-31 | 中国石油化工股份有限公司 | Method for determining stratum fracturing property based on tensile fracture and shear fracture |
| CN108009705B (en) * | 2017-11-07 | 2021-05-14 | 中国石油大学(华东) | Shale reservoir compressibility evaluation method based on support vector machine technology |
| CN111289368B (en) * | 2018-12-06 | 2022-08-05 | 中国石油天然气股份有限公司 | Method for evaluating fracturing performance based on energy conservation in hydraulic fracturing physical process |
| CN110529088A (en) * | 2019-08-30 | 2019-12-03 | 西南石油大学 | A kind of rock compressibility section method for building up based on thin section identification |
| CN111425193B (en) * | 2020-01-21 | 2020-12-01 | 东北石油大学 | Reservoir compressibility evaluation method based on clustering analysis logging rock physical facies division |
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| CN103308946B (en) * | 2013-05-14 | 2016-08-31 | 中国科学院武汉岩土力学研究所 | A kind of geological extra-forecast method entering information based on blasthole drilling |
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