CN105626009A - Fracture-cavern type carbonate oil reservoir single well water injection oil substituting effect quantitative evaluation method - Google Patents
Fracture-cavern type carbonate oil reservoir single well water injection oil substituting effect quantitative evaluation method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 49
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- 235000020681 well water Nutrition 0.000 title claims abstract description 37
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- 238000002347 injection Methods 0.000 title claims abstract description 18
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 52
- 238000011161 development Methods 0.000 claims description 26
- 239000000470 constituent Substances 0.000 claims description 11
- 239000003129 oil well Substances 0.000 claims description 10
- 238000011084 recovery Methods 0.000 claims description 10
- 230000004044 response Effects 0.000 claims description 8
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- 201000008827 tuberculosis Diseases 0.000 claims description 8
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- 239000011229 interlayer Substances 0.000 claims description 6
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- 239000012530 fluid Substances 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 5
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- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
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- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
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Abstract
The invention provides a fracture-cavern type carbonate oil reservoir single well water injection oil substituting effect quantitative evaluation method. The method comprises the following steps that a hierarchical fuzzy subset is set up, quantitative evaluation of the membership degree of all grades of evaluation elements is conducted, and a membership matrix S is obtained; the weight function of all the evaluation elements is determined, and an elevation weight vector A is obtained; the elevation weight vector A and the membership matrix S are calculated by using a fuzzy transformation mathematic model, and a fuzzy comprehensive evaluation measure value vector quantity B is obtained; and a final comprehensive evaluation result is determined through the maximum membership principle. The hierarchical fuzzy subset comprises an evaluation element set U and an evaluation set V. The corresponding expression of the fuzzy transformation mathematic model is shown in the specification, wherein b is a membership degree belonging to a j<th> grade evaluation effect, and ai is the weight value of an i<th> elevation element; sij is a membership degree that the i<th> elevation element belongs to the j<th> grade evaluation effect; p is the number of elevation elements in the evaluation element set U; m is the dimension number of the evaluation set V.
Description
Technical field
The invention belongs to reservoir water for oil development field, relate to a kind of comprehensive difference dynamic static data quantitative evaluation individual well water filling method for oil development effectiveness, particularly a kind of fractured-cavernous carbonate reservoir individual well water filling is for oil effect quantitatively evaluation methodology.
Background technology
Fractured-cavernous carbonate reservoir reservoir space type is various, anisotropism is particularly thorny, oil water relation is complicated, and such complex reservoir still suffers from many difficult problems in Efficient Development, scale in building product and stable yields, layer description and fluid flowing law analysis, raising recovery ratio etc. At present, individual well water filling has become domestic fractured-cavernous carbonate reservoir for oil and has improved the dominant technology of recovery ratio further. Although water filling achieves very significant oil increasing effect for the on-the-spot application of oil, but how comprehensively dynamic static data quantitative assessment individual well water filling accurately is for oil development effectiveness, thus to selecting suitable countermeasure of optimizing and revising to provide the research work of foundation not yet to carry out.
Domestic to individual well water filling for oil development effectiveness evaluation analysis rely primarily on experience, subjectivity is strong and is only capable of considering single attribute factor, impact such as ton oil water consumption rate, handle up round, oil increment etc., when lacking priori understanding, it is difficult to the real features of the different classes of sample set of Quantitative study. And owing to individual well water filling belongs to domestic special technology for oil, abroad not yet have the fractured-cavernous carbonate reservoir individual well water filling example for oil. Fuzzy comprehensive evoluation is a kind of comprehensive estimation method based on fuzzy mathematics, qualitative evaluation is converted into quantitative assessment according to the degree of membership theory of fuzzy mathematics by it, namely adopt fuzzy mathematics that the things or object that are subject to multifactor collaborative restriction are carried out a kind of overall evaluation, have the advantages that result is clear, systematicness is strong, it is adaptable to various fuzzy, be difficult to the uncertainty challenge that quantifies. But, due to determine each factor index affect important order, the factor of evaluation centralization of state power reset put etc. in too much rely on subjective judgment, it is poor that the theoretical fractured-cavernous carbonate reservoir individual well water fillings many for media type, that different scale is big of traditional fuzzy evaluation evaluate adaptability for oil effect quantitatively. Present stage, set up a set of workable fractured-cavernous carbonate reservoir individual well water filling for oil effect quantitatively evaluation methodology, be still a technical barrier urgently to be resolved hurrily greatly.
Summary of the invention
In order to solve the problems referred to above, it is an object of the invention to provide a kind of fractured-cavernous carbonate reservoir individual well water filling in conjunction with principal component analysis, step analysis and fuzzy comprehensive evoluation method for quantitatively evaluating for oil development effectiveness. The limitation of subjective judgment is too much depended in this assessment method can overcome traditional fuzzy evaluation method determining important order that factor index affects, the weight of factor of evaluation is arranged etc., the development effectiveness of oil is replaced in real comprehensive dynamic static data quantitative evaluation individual well water filling, thus for selecting the countermeasure of optimizing and revising being suitable for provide foundation.
In order to achieve the above object, the present invention provides a kind of fractured-cavernous carbonate reservoir individual well water filling for oil effect quantitatively evaluation methodology, comprises the following steps:
Build grade fuzzy subset, the degree of membership of quantitatively characterizing factor of evaluation at different levels, it is thus achieved that subordinated-degree matrix S;
Determine the weight of each factor of evaluation, it is thus achieved that pass judgment on weight vectors A;
Utilize blurring mapping mathematical model that described judge weight vectors A and described subordinated-degree matrix S is calculated, it is thus achieved that the measure value vector B of fuzzy overall evaluation;
Adopt maximum membership grade principle, it is determined that final comprehensive evaluation result;
Wherein, described grade fuzzy subset includes factor of evaluation collection U and Comment gathers V;
The expression formula that described blurring mapping mathematical model is corresponding is:
B is the degree of membership being under the jurisdiction of jth grade evaluation effect; aiWeighted value for i-th factor of evaluation; sijThe degree of membership of jth grade evaluation effect it is under the jurisdiction of for i-th factor of evaluation; P is the number of factor of evaluation in described factor of evaluation collection U; M is the dimension of Comment gathers V.
In above-mentioned evaluation methodology, it is preferred that described factor of evaluation collection U includes one-level factor of evaluation collection and the two-level appraisement set of factors of each one-level factor of evaluation.
In above-mentioned evaluation methodology, it is preferred that described one-level factor of evaluation include statically quality factor, exhaustion Exploitation Status, injection parameter, Indexes of Evaluation Effect;
The two-level appraisement factor of described quality factor statically includes drilling well wastage, reservoir space type, Reservoir Body closure, dynamic geological reserves, heat-supplied, water body multiple;
The two-level appraisement factor of described exhaustion Exploitation Status includes before Output response feature, water breakthrough characteristics, tuberculosis recovery percent of reserves before moisture content, tuberculosis;
The two-level appraisement factor of described injection parameter includes diurnal injection, cyclic waterflooding time, stewing well time in cycle, handles up round at present;
The two-level appraisement factor of described Indexes of Evaluation Effect includes ton oil water consumption rate, accumulation injection water retaining in reservoir, cumulative voidage replacement ratio, raising recovery ratio value.
In above-mentioned evaluation methodology, it is preferred that it is good, better, general, poor that described Comment gathers V includes comment.
In above-mentioned evaluation methodology, it is preferred that the method for the weight of each factor of evaluation of described acquisition comprises the following steps:
Obtain the dynamic static data of oil well to be measured, set up assessment indicator system, and be standardized processing to the index value of each factor of evaluation;
Analyze each factor of evaluation and individual well water filling is replaced the affecting laws of oil development effectiveness, it is determined that its dependency;
Adopt PCA to determine the correlation coefficient of each factor of evaluation, and it is ranked up;
Adopt analytic hierarchy process (AHP) to calculate all grading factors and individual well water filling is replaced the weighing factor of oil development effectiveness.
In above-mentioned evaluation methodology, it is preferred that described standard diagrams system includes the first level factor index and the second level factor index;
Described the first level factor index is selected from described one-level factor of evaluation collection; Described the second level factor index is selected from described two-level appraisement set of factors.
In above-mentioned evaluation methodology, it is preferred that the method for described standardization is normalized.
In above-mentioned evaluation methodology, it is preferred that individual well water filling is replaced the affecting laws of oil development effectiveness to include following rule by described each factor of evaluation:
Reservoir Body closure is good, and water filling is affected little for oil well by structure limitation, and failure risk is low;
Reservoir Body closure is poor, then often there is multiple Reservoir Body feed flow, is affected by structure limitation, if communicating passage water logging after water filling, most of surplus oil will be unable to extraction, and water filling will be lost efficacy rapidly for oil well;
For the well of obvious emptying or severe leakage, initial stage daily fluid production rate is high, substantially can be identified as brill and has met cave type Reservoir Body, and the Output response of exhaustion exploitation meets slow decreasing characteristic;
Single well-controlled dynamic geological reserves are relatively big, Reservoir Body closure is good and water body aplasia, and oil pressure drops and meets linear relationship with tired Liquid output curve, and water filling oil increasing effect is notable, can show that displacement is fast, rule that to boil in a covered pot over a slow fire the well time shorter in production process;
For slit formation and the hole type reservoir of poor connectivity, injecting water can form certain displacement in acid etching slot apertures near shaft bottom, natural pore, but daily water-injection rate is low (is generally less than 200m3/ d), the cycle boils in a covered pot over a slow fire well time length (more than 15d), and water filling, for oil effectively round few (taking turns less than 5), increases oil limited (less than 1000t);
For there is the fracture and cave reservoir of energy supply, it is not single linear relationship that oil pressure drops with tired Liquid output, and high intensity water filling easily forms secondary water cone, having a big risk of water filling inefficient cycle near wellbore zone, need to consider water filling carefully for oil exploitation. Fig. 2 A and Fig. 2 B represents constant volume cave type fracture and cave reservoir respectively and there is the oil pressure of fracture and cave reservoir of energy supply and drop-tire out production fluid variation characteristic curve chart.
In above-mentioned evaluation methodology, it is preferred that described dependency includes positive correlation and negative correlation.
In above-mentioned evaluation methodology, it is preferred that described PCA comprises the following steps:
Set up the standardization covariance coefficient matrix of factor of evaluation; Ask for eigenvalue and the corresponding orthogonalization unit character vector of described covariance coefficient matrix; Calculate variance contribution ratio and the cumulative proportion in ANOVA of main constituent; Calculate main constituent load; Calculate principal component scores coefficient; Described principal component scores coefficient is the correlation coefficient of each factor of evaluation.
In above-mentioned evaluation methodology, it is preferred that described analytic hierarchy process (AHP) comprises the following steps:
According to the 1-9 ratio scale in analytic hierarchy process (AHP), the correlation coefficient of each factor of evaluation after sequence is compared between two, obtain the judgment matrix of quantification;
Aver-age Random Consistency Index RI is utilized to check whether described judgment matrix meets concordance; If the concordance of being unsatisfactory for, then revise the ratio scale of relevant evaluation factor in described judgment matrix, until described judgment matrix meets consistency check; If described judgment matrix meets concordance, then ask for eigenvalue of maximum and the characteristic vector thereof of described judgment matrix;
Described characteristic vector is described judge weight vectors A.
The present invention also provides for above-mentioned evaluation methodology in fractured-cavernous carbonate reservoir individual well water filling for the application in oil exploitation.
In above-mentioned application, preferably, described fractured-cavernous carbonate reservoir is the fracture-cavity type carbonate reservoir of Ordovician system interlayer karst-Fracture Control, more preferably the fracture-cavity type carbonate reservoir oil field of Tarim Basin Ordovician system interlayer karst-Fracture Control or the fracture-cavity type carbonate reservoir of middle petrochemical industry Tahe Ordovician system interlayer karst-Fracture Control.
Accompanying drawing explanation
Fig. 1 is the Technology Roadmap of embodiment 1.
Production fluid variation characteristic curve chart drops-tires out in the oil pressure that Fig. 2 A is constant volume cave type fracture and cave reservoir.
Production fluid variation characteristic curve chart drops-tires out in the oil pressure that Fig. 2 B is the fracture and cave reservoir that there is energy supply.
Fig. 3 is correlation coefficient and the significance level ordering chart thereof that in embodiment 1, oil development effect influence is replaced in water filling by each the second level factor index.
Fig. 4 is the 36 mouthfuls of water fillings of the Tarim Oilfield typical case's fractured-cavernous carbonate reservoir development response evaluation result figure for oil individual well.
Detailed description of the invention
In order to the technical characteristic of the present invention, purpose and beneficial effect are more clearly understood from, existing technical scheme is carried out described further below, but it is not intended that can the restriction of practical range to the present invention.
As it is shown in figure 1, the method for quantitatively evaluating of the present invention carries out generally according to following steps, initially set up the fracture-pore reservoir individual well water filling of set of system for oil Effect Evaluation Index System, be then standardized the index value of each factor of evaluation processing; The single factors index affecting laws to development effectiveness in this index system of analyzing and researching; The score coefficient of the main constituent variance contribution to each evaluation index and main constituent is calculated by principal component analytical method, thus the important order of impact obtaining each factor index; On this basis, binding hierarchy analyzes method and fuzzy comprehensive evoluation sets up individual well water filling for oil effect comprehensive quantitative assessment model, Synthetic Measurement value under the multifactor collaborative impact of quantitative evaluation, a kind of workable fractured-cavernous carbonate reservoir individual well water filling of final proposition is for oil effect quantitatively evaluation methodology, and is applied in the evaluation that mining site is actual.
Embodiment 1
The individual well water filling of Tarim Oilfield Ordovician system M fractured-cavernous carbonate reservoir is carried out quantitative assessment for oil development effectiveness by the present embodiment. This oil reservoir mainly effective reservoir space includes large-scale cave, secondary corrosion hole and high angle fracture etc., belong to non-saturated reservoir, difference between reservoir pressure and saturation pressure is big, between 35-66MPa, average 50.5MPa, in-place oil be mainly low viscosity, low-sulfur, in light crude oil containing colloid-asphalitine, high-content wax, density 0.82-1.10g/cm3, volume factor 1.04-1.66, mean reservoir pressure 73.3MPa, average formation temperature 154.4 DEG C, for normal temperature-pressure system.
The present embodiment have chosen 36 mouthfuls of representative water fillings of Tarim Oilfield M fractured-cavernous carbonate reservoir and replaces the dynamic static data of oil individual well to set up grade fuzzy subset, defines one-level factor of evaluation collection: U={U1, U2, U3, U4}={ be quality factor statically, exhaustion Exploitation Status, injection parameter, Indexes of Evaluation Effect }, for these 4 one-level grading factors of accurate description, it is further divided into following two-level appraisement factor respectively: U1={ U11, U12, U13, U14, U15, U16}={ drilling well wastage, reservoir space type, Reservoir Body closure, dynamic geological reserves, heat-supplied, water body multiple }; U2={ U21, U22, U23, U24}={ Output response feature, water breakthrough characteristics, moisture content before tuberculosis, recovery percent of reserves before tuberculosis }; U3={ U31, U32, U33, U34}={ diurnal injection, the cyclic waterflooding time, the cycle boils in a covered pot over a slow fire well time, round of handling up at present }; U4={ U41, U42, U43, U44}={ ton oil water consumption rate, accumulation injection water retaining in reservoir, cumulative voidage replacement ratio, improve recovery ratio amplitude }. In conjunction with actual mining site, individual well water filling is divided into 4 big classes for oil development effectiveness: good, better, general, poor, sets up the Comment gathers of fuzzy comprehensive evoluation: V={ is good, better, generally, poor.
Grade fuzzy subset according to above-mentioned foundation, the individual well water filling that the present embodiment is set up has 4 the first level factor indexs and 18 the second level factor indexs for oil Effect Evaluation Index System, and table 1 gives the individual well water filling Effect Evaluation Index System for oil and the impact on development effectiveness of the index value thereof.
Table 1
Remarks: DiExpression initial stage lapse rate
Table 1 illustrates each single factors index value simultaneously and water filling is replaced the affecting laws of oil effect. As Reservoir Body closure is good, water filling is affected little for oil well by structure limitation, and failure risk is low; As poor in Reservoir Body closure, then often there is multiple Reservoir Body feed flow, affected by structure limitation, if communicating passage water logging after water filling, most of surplus oil will be unable to extraction, and water filling will be lost efficacy rapidly for oil well.
In addition, well for obvious emptying or severe leakage, initial stage daily fluid production rate is high, substantially can be identified as brill and meet cave type Reservoir Body, the Output response of exhaustion mining phase meets slow decreasing characteristic, if single well-controlled dynamic geological reserves are relatively big, Reservoir Body closure is good and water body aplasia, oil pressure drops and meets linear relationship with tired Liquid output curve, individual well water filling oil increasing effect is notable, can show the rule that displacement is fast, the stewing well time in cycle is shorter in production process; For slit formation and the hole type reservoir of poor connectivity, inject water and acid etching slot apertures near shaft bottom, natural pore can form certain metathesis, but daily water-injection rate is low (is generally less than 200m3/ d), the cycle boils in a covered pot over a slow fire the well time longer (more than 15d), effective round few (taking turns less than 5), increases oil limited (less than 1000t); For there is the fracture and cave reservoir of energy supply, it is not single linear relationship that oil pressure drops with tired Liquid output curve, and high intensity water filling easily forms secondary water cone, having a big risk of water filling inefficient cycle near wellbore zone, need to consider individual well water filling carefully for oil exploitation. Fig. 2 A and Fig. 2 B represents constant volume cave type fracture and cave reservoir respectively and there is the oil pressure of fracture and cave reservoir of energy supply and drop-tire out production fluid variation characteristic curve chart.
In his-and-hers watches 1, each factor index carries out the min-max standardization of routine, and each single factors index value of providing of associative list 1 is to the individual well water filling affecting laws for oil development effectiveness, determine the dependency of each factor index, then the thinking of the dimensionality reduction of PCA is utilized, by the dependence within original variable correlation matrix, the variable that some are had intricate relation is attributed to a few multi-stress, sets up the standardization covariance coefficient matrix R=(H of factor of evaluationef)q��q, its expression formula is:
In this expression formula, R is covariance matrix; HefCorresponding element is arranged for the e row in covariance matrix and f; E is line number; F is columns; Q is the dimension of matrix; N is number of samples; K is sample variable value; xkeFor the value of e variable in kth sample;For the meansigma methods of e variable in all samples; xkfFor the value of f variable in kth sample;For the meansigma methods of f variable in all samples.
By calculating the score coefficient of the main constituent variance contribution to each evaluation index and main constituent, i.e. correlation coefficient between main constituent and evaluation index, it is embodied as step and is: calculate eigenvalue and the corresponding orthogonalization unit character vector of this standardization covariance coefficient matrix R; Calculate variance contribution ratio and the cumulative proportion in ANOVA of main constituent; Calculate main constituent load; Calculating principal component scores coefficient, this score coefficient is the correlation coefficient of each factor of evaluation.
Result of calculation according to principal component analysis, obtain the correlation coefficient of each the second level factor index, determine each the second level factor index important order of impact on development effectiveness, order is affected as shown in Figure 3 to secondary by main, it is followed successively by: improve recovery ratio value, handle up at present round, Output response feature, water body multiple, ton oil water consumption rate, cycle boils in a covered pot over a slow fire the well time, dynamic geological reserves, water breakthrough characteristics, moisture content before tuberculosis, heat-supplied, daily water-injection rate, accumulation injection water retaining in reservoir, cumulative voidage replacement ratio, reservoir space type, Reservoir Body closure, the cyclic waterflooding time, recovery percent of reserves before tuberculosis, drilling well wastage.
Result of calculation according to above-mentioned assessment indicator system and principal component analysis, application level analytic process determines that individual well water filling is replaced the weighing factor of oil development effectiveness by whole factor index, the steps include:
According to the Saaty 1-9 ratio scale proposed, each factor index is compared between two, respectively obtains the first level factor index judgment matrix of quantizationWith the second level factor index judgment matrix WithOn this basis, utilize whether coincident indicator RI test matrix meets coherence request: if meeting, characteristic of correspondence vector is required judge weight sets; If being unsatisfactory for, factor index U in judgment matrix need to be remodifiediAbout factor index UjRatio scale mij, until meeting consistency check. Solving the eigenvalue of maximum of this judgment matrix meeting consistency check, its characteristic of correspondence vector is required judge weight vectors A. Table 2 replaces the weighted value of factor indexs at different levels in oil assessment indicator system for the Tarim Oilfield Ordovician system M fractured-cavernous carbonate reservoir individual well water filling that application level analytical calculation obtains. As shown in Table 2,Judge weight vectorsFor (0.055,0.117,0.262,0.566);Judge weight vectorsFor (0.06,0.06,0.13,0.03,0.25,0.47);Judge weight vectorsFor (0.53,0.21,0.21,0.05);Judge weight vectorsFor (0.12,0.06,0.26,0.56);Judge weight vectorsFor (0.28,0.07,0.07,0.58).
Table 2
Grade fuzzy subset according to above-mentioned structure, in conjunction with fuzzy statistics and dualistic contrast compositor, the dissimilar water filling probability size for oil comment effect is determined in the contrast between two between multiple factor indexs, thus the degree of membership of quantitatively characterizing factor of evaluation at different levels, obtain subordinated-degree matrix S, then utilize the weighted average Fuzzy Arithmetic Operators of blurring mapping mathematical model
Weight vectors by above-mentioned the second level factor index (i.e. two-level appraisement factor)Corresponding subordinated-degree matrixBeing combined computing, wherein, b is the degree of membership being under the jurisdiction of jth grade evaluation effect; aiForThe weighted value of middle i-th the second level factor index; sijForMiddle i-th the second level factor index is under the jurisdiction of the degree of membership of jth grade evaluation effect, and it can be inquired about in table 3; P is the number of factor index in corresponding the second level factor index set (i.e. two-level appraisement set of factors); M is the dimension of Comment gathers V. In like manner, more respectively incite somebody to actionCorresponding subordinated-degree matrix It is combined computing, the measure value vector B of the final fuzzy evaluation obtaining all the second level factor indexs2=(b)1��m, B2The contained number being subordinate to angle value is identical with the number of the first level factor index (i.e. one-level factor of evaluation).
Table 3 is each factor of evaluation degree of membership table in different indication ranges, sijThe degree of membership obtaining each factor of evaluation is searched in table 3 according to practical situation.
Table 3
By above-mentioned measure value vector B2Subordinated-degree matrix as above-mentioned the first level factor indexThe weighted average Fuzzy Arithmetic Operators of recycling blurring mapping mathematical model
By above-mentionedThe weight vectors of corresponding the first level factor indexBeing combined computing, wherein, b is the degree of membership being under the jurisdiction of jth grade evaluation effect; aiForThe weighted value of middle i-th the first level factor index; sijForMiddle i-th the first level factor index is under the jurisdiction of the degree of membership of jth grade evaluation effect; P is the number of factor index in corresponding the first level factor index set; M is the dimension of Comment gathers V, obtains the measure value vector B of final fuzzy evaluation, finally, applies maximum membership grade principle, individual well water filling is replaced the overall merit of oil development effectiveness.
Embodiment 2
Utilize the weighted average Fuzzy Arithmetic Operators of blurring mapping mathematical model
Wherein, b is the degree of membership being under the jurisdiction of jth grade evaluation effect; aiWeighted value for i-th factor of evaluation; sijThe degree of membership of jth grade evaluation effect it is under the jurisdiction of for i-th factor of evaluation; P is the number of factor of evaluation in described factor of evaluation collection U; M is the dimension of Comment gathers V. The each oil well individual well water filling in full oil field is first replaced the second level factor index of oil development effectiveness carry out fuzzy evaluation, then the first level factor index of each oil well is carried out fuzzy overall evaluation. Fig. 4 is the 36 mouthfuls of water fillings of the Tarim Oilfield Ordovician system M fractured-cavernous carbonate reservoir evaluation results for oil well. Table 4 gives the wherein 4 mouthfuls of typical water fillings factor index value for oil well and effect assessment result. Wherein, the measure value vector B of the first level factor index of W1 is (0.67,0.14,0.086,0.092), and according to maximum membership grade principle, what the comprehensive evaluation result of W1 was corresponding is the first dimension comment in Comment gathers, namely effective; In like manner, the second dimension comment that grading that what the comprehensive evaluation result of W2 was corresponding is is concentrated, namely effect is better; The third dimension comment that grading that what the comprehensive evaluation result of W3 was corresponding is is concentrated, namely effect is general; The fourth dimension comment that grading that what the comprehensive evaluation result of W4 was corresponding is is concentrated, i.e. weak effect.
Table 4
In sum, the comprehensive multiple dynamic static data of method for quantitatively evaluating provided by the invention, propose the water filling of set of system for oil development response evaluation index system, the basis of each factor index affecting laws adopt principal component analytical method determine the important order of impact of each factor index studying, overcome conventional Judgement Method and determining that factor index affects important order, the aspects such as factor of evaluation weight is arranged too much depend on the limitation of subjective judgment, really solve in actual mining site and how comprehensively to move the static data quantitative evaluation individual well water filling technical barrier for oil effect, and it is high to evaluate accuracy rate. utilize this method for quantitatively evaluating to each water filling for after oil development effect overall merit, can different development phases residing for low yield poor efficiency water injection well and potentiality of remaining oil, what formulation was suitable optimizes and revises countermeasure, it is thus possible at the scene application obtains significant oil increasing effect, the residual production potential of the mining-employed reserves of taping the latent power better.
Claims (10)
1. the water filling of fractured-cavernous carbonate reservoir individual well is for an oil effect quantitatively evaluation methodology, comprises the following steps:
Build grade fuzzy subset, the degree of membership of quantitatively characterizing factor of evaluation at different levels, it is thus achieved that subordinated-degree matrix S;
Determine the weight of each factor of evaluation, it is thus achieved that pass judgment on weight vectors A;
Utilize blurring mapping mathematical model that described judge weight vectors A and described subordinated-degree matrix S is calculated, it is thus achieved that the measure value vector B of fuzzy overall evaluation;
Adopt maximum membership grade principle, it is determined that final comprehensive evaluation result;
Wherein, described grade fuzzy subset includes factor of evaluation collection U and Comment gathers V;
The expression formula that described blurring mapping mathematical model is corresponding is:
B is the degree of membership being under the jurisdiction of jth grade evaluation effect; aiWeighted value for i-th factor of evaluation; sijThe degree of membership of jth grade evaluation effect it is under the jurisdiction of for i-th factor of evaluation; P is the number of factor of evaluation in described factor of evaluation collection U; M is the dimension of Comment gathers V.
2. evaluation methodology according to claim 1, it is characterised in that: described factor of evaluation collection U includes one-level factor of evaluation collection and the two-level appraisement set of factors of each one-level factor of evaluation.
3. evaluation methodology according to claim 2, it is characterised in that: described one-level factor of evaluation include statically quality factor, exhaustion Exploitation Status, injection parameter, Indexes of Evaluation Effect;
The two-level appraisement factor of described quality factor statically includes drilling well wastage, reservoir space type, Reservoir Body closure, dynamic geological reserves, heat-supplied, water body multiple;
The two-level appraisement factor of described exhaustion Exploitation Status includes before Output response feature, water breakthrough characteristics, tuberculosis recovery percent of reserves before moisture content, tuberculosis;
The two-level appraisement factor of described injection parameter includes diurnal injection, cyclic waterflooding time, stewing well time in cycle, handles up round at present;
The two-level appraisement factor of described Indexes of Evaluation Effect includes ton oil water consumption rate, accumulation injection water retaining in reservoir, cumulative voidage replacement ratio, raising recovery ratio value.
4. the evaluation methodology according to any one of claim 1-3, it is characterised in that: it is good, better, general, poor that described Comment gathers V includes comment.
5. the evaluation methodology according to any one of claim 1-4, it is characterised in that: the method for the weight of each factor of evaluation of described acquisition comprises the following steps:
Obtain the dynamic static data of oil well to be measured, set up assessment indicator system, and be standardized processing to the index value of each factor of evaluation;
Analyze each factor of evaluation and individual well water filling is replaced the affecting laws of oil development effectiveness, it is determined that its dependency;
Adopt PCA to determine the correlation coefficient of each factor of evaluation, and it is ranked up;
Adopt analytic hierarchy process (AHP) to calculate whole factors of evaluation and individual well water filling is replaced the weighing factor of oil development effectiveness.
6. evaluation methodology according to claim 5, it is characterised in that: described standard diagrams system includes the first level factor index and the second level factor index;
Described the first level factor index is selected from described one-level factor of evaluation collection; Described the second level factor index is selected from described two-level appraisement set of factors.
7. the evaluation methodology according to claim 5 or 6, it is characterised in that: described PCA comprises the following steps:
Set up the standardization covariance coefficient matrix of factor of evaluation; Ask for eigenvalue and the corresponding orthogonalization unit character vector of described covariance coefficient matrix; Calculate variance contribution ratio and the cumulative proportion in ANOVA of main constituent; Calculate main constituent load; Calculate principal component scores coefficient; Described principal component scores coefficient is the correlation coefficient of each factor of evaluation.
8. the evaluation methodology according to any one of claim 5-7, it is characterised in that: described analytic hierarchy process (AHP) comprises the following steps:
According to the 1-9 ratio scale in analytic hierarchy process (AHP), the correlation coefficient of each factor of evaluation after sequence is compared between two, obtain the judgment matrix of quantification;
Aver-age Random Consistency Index RI is utilized to check whether described judgment matrix meets concordance; If the concordance of being unsatisfactory for, then revise the ratio scale of relevant evaluation factor in described judgment matrix, until described judgment matrix meets consistency check; If described judgment matrix meets concordance, then ask for eigenvalue of maximum and the characteristic vector thereof of described judgment matrix;
Described characteristic vector is described judge weight vectors A.
9. the application in fractured-cavernous carbonate reservoir individual well water filling is developed for oil of the evaluation methodology described in any one of claim 1-8.
10. application according to claim 9, it is characterized in that: described fractured-cavernous carbonate reservoir is the fracture-cavity type carbonate reservoir of Ordovician system interlayer karst-Fracture Control, it is preferred to the fracture-cavity type carbonate reservoir oil field of Tarim Basin Ordovician system interlayer karst-Fracture Control or the fracture-cavity type carbonate reservoir of middle petrochemical industry Tahe Ordovician system interlayer karst-Fracture Control.
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