CN107944749A - A kind of shale gas block exploitation potential assessment method based on relatively preferred index - Google Patents
A kind of shale gas block exploitation potential assessment method based on relatively preferred index Download PDFInfo
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Abstract
The present invention discloses a kind of shale gas block exploitation potential assessment method based on relatively preferred index, and this method includes collecting the Enrichment And Reservoiring of shale gas research block and exploitation key element, collects basic data data；Establish governing factor relation flow graph；Ask for the influence distribution of governing factor；Establish evaluation points vector；The Calculation Estimation factor compares redistribution；Good and bad degree distribution of the contrast block under each evaluation points is calculated respectively；Good and bad degree reliability distribution of the contrast block under each evaluation points is calculated respectively；Calculate relatively preferred index COI；The present invention establishes the relative evaluation theoretical system that dynamic calculates, relatively preferred index COI is calculated with more governing factor collectives difference, overall merit is carried out to constituency by COI numerical values reciteds, for Geological background, different blocks, compare to different degree of prospecting and provide unified method, shale gas Enrichment And Reservoiring possibility and exploitability are also taken into account, relatively reliable solution is provided for the preferred area's overall merit of shale gas.
Description
Technical field
The present invention relates to oil-gas exploration and development technical field, more specifically for be a kind of page based on relatively preferred index
Rock gas block exploitation potential assessment method.Suitable for shale gas block exploration-development potential evaluate, be particularly suitable for shale gas into
The Favorable Areas overall merit in ripe exploratory area.
Background technology
In recent years, shale gas exploitation is considered as a revolution in global energy field, can not only greatly improve national energy
The source degree of self-sufficiency, and national energy consumption structure can be changed.In view of the status that shale gas becomes more and more important, to reach more accurately
Shale gas block Potential Evaluation, has emerged in large numbers the new technology side in multinomial professional domain in the related disciplines such as geology, physical prospecting in recent years
Method：Such as based on the firsthand information of region with reference to Petroleum System analogue technique shale Comprehensive Evaluation of Fine Varietal Resources method,
GeoSphere oil reservoirs are with brill surveying and mapping technology, nuclear magnetic resonance Factor Analysis Technique, seismic data pre-stack seismic road treatment technology, survey
Well data function principal component analysis technology etc..
Shale gas exploration-development potential appraisal at this stage, more based on to obtain important parameter technical research,
Further investigation is supported by relevant speciality technological progress or the application of new technology, it is rarer to the perfect of appraisement system.With
Toward research in there is following problem not cause abundant attention：
1. compared to the U.S., also in early stage, the development much to work needs to borrow for Chinese shale gas exploration and development
The mature experience in the mirror U.S..But the shale gas geological conditions difference of two countries is larger, and how is the shale gas system of Geological background
Scientifically contrast and therefrom to refer to information be vital for acquisition；
2. in the case where lacking complete geologic rule and disclosing, block absolute evaluation system is established, is dived to shale gas exploration and development
Whether force estimation has directive significance；
3. in the comparative analysis work of correlative factor, gone to represent block synthesis effect with the individual sex differernce of isolated factor
Should, whether the result so obtained is reasonable.
On the premise of Shale Gas Accumulation theoretical system is constant, withe technology is deeply promoted, but lacks perfect evaluation
Architectural study, constituency overall merit work is done under such thinking framework, encounters following difficulty：
1. the work of selection Dominated Factors excessively relies on experience, there is very strong subjectivity.
2. after surely multiple Dominated Factors are selected, relation is considerably complicated between Dominated Factors, interacts and can not be independent
Exclude.
3. the influence between most of factor does not have clear and definite functional relation to describe.
4. the Dominated Factors that can quantify to compare only account for seldom a part of in all factors.
5. in the comparative analysis work with Dominated Factors in historical summary, it is easily trapped into for the larger factor of otherness
Compare and analyze, and nonsystematic is integrally studied.
6. in measurable, calculating, the factor quantified, the source of data, the result calculated is with uncertainty, such as passes through
The data that the means such as well logging, well logging, seismic prospecting, laboratory measurement are obtained, to characterize correlative factor, these data are because of difference
The difference of reliability caused by block or different obtaining means is ignored.
Favorable Areas is integrated, it is necessary in terms of shale gas Enrichment And Reservoiring and exploitability with difficult in view of problem above
Evaluation method is improved, and under the frame of Shale Gas Accumulation theory, makes that the logic of appraisement system is tighter, and method is more reasonable,
To provide reliable basis with constituency overall merit for the assessment of shale gas exploration-development potential.
The content of the invention
In order to overcome the shortcoming of above-mentioned background technology, the purpose of the present invention is deposited in the existing integrated evaluating method of analysis
On the basis of problem, it is proposed that a kind of shale gas block exploitation potential assessment method based on relatively preferred index.This method
A set of method for carrying out grading evaluation to constituency by the relatively preferred index of calculating is established, for Geological background, no
Compare to same block, different degrees of prospecting, there is provided unified integrated evaluating method system.
To achieve these goals, technical solution provided by the invention is as follows：
A kind of shale gas block exploitation potential assessment method based on relatively preferred index, including step in detail below：
Step 1：The Enrichment And Reservoiring and exploitation key element of shale gas research block are collected, source includes but not limited to：Hydrocarbon energy
Power, reservoir storage and collection performance, easily gas reservoir cap rock condition, exploitation property.Basic data data are collected to include but not limited to：Physical prospecting, drilling well,
Well logging, geologic information.
Step 2：Establish governing factor relation flow graph.
Step 3：Ask for the influence distribution of governing factor in relation flow graph.Wherein, step 3 includes 3 step by step：
The corresponding adjacency matrix M1 of 3.1 opening relationships flow graphs；
3.2 using between 0 to 1 and level off to 0 decimal correction matrix M1 in numerical value as 0 element, it is and basic herein
On establish frequency distribution matrix M2；
3.3 calculate the influence distribution for asking for governing factor using power iteration method.
Step 3 illustrates 1：Matrix, element are mathematically defined concept；Adjacency matrix method for building up, power iteration
Method is known method mathematically.
Step 3 illustrates 2：Frequency distribution matrix M2 method for building up：Matrix M1 after correcting 0 value, by each of which element
Divided by the sum of all elements for being expert at of the element, element of the obtained new value as same position in frequency distribution matrix M2.
Step 4：Establish evaluation points vector V1.
Step 4 illustrates 1：Vector is mathematically defined concept.
Step 4 illustrates 2：Evaluation points vector V1 method for building up：The factor conduct for participating in contrast is extracted in governing factor
Evaluation points, vector element are made of successively corresponding influence distribution values.
Step 5：The Calculation Estimation factor is than redistribution Wf.Wherein, step 5 includes 3 step by step：
5.1 structure comparator matrix M3：Using evaluation points vector V1 as column vector, by the structure reciprocal of each element of V1 vectors
Into vectorial V2 as row vector, be multiplied by row vector with column vector and obtain comparator matrix M3；
The element for being more than 9 in comparator matrix M3 is replaced with 9 by 5.2, and the element between 1 and 9 rounds up；Change matrix
Element is less than 1 element：If aijIt is the element in matrix M3, lower label i, j is is expert at and column here, if aij<1, then
Its value is revised as 1/aji。。
The corresponding feature vector w1 of 5.3 solution matrix M3 maximum eigenvalue, and by each element in feature vector w1 divided by
The sum of w1 all elements, obtained new value is as evaluation points proportion distribution vector WfThe element numerical value of middle same position, so that
Obtain evaluation points proportion distribution vector Wf。
Step 5 explanation：Characteristic value, feature vector are mathematically defined concept.
Step 6：Good and bad degree distribution D of the contrast block under each evaluation points is calculated respectively.Wherein, step 6 includes 4
It is a step by step：
If 6.1 k-th evaluation points can only qualitative measure, compared two-by-two by block, establish k-th of evaluation points
Block contrast matrix, be denoted as M4k, lower label k is meant that the corresponding sequence number of evaluation points；Solve M4kMaximum eigenvalue corresponds to
Feature vector, be denoted as w2k, according to step 5.3 same procedure to feature vector w2kCalculate, obtain under k-th of evaluation points
Block quality degree is distributed Dk。
If 6.2 k-th of evaluation points can be with quantitative measurement, and is characterized by frequency, then DkEach element
Value be the sum of current frequency divided by all frequencies.
If 6.3 k-th of evaluation points can be with quantitative measurement, and is characterized by property value size, then first carry out
Min-Max is standardized, then builds matrix M4k：If the data set after standardization is vector V3, as column vector, vectorial V3 is every
The vectorial V4 reciprocal formed of a element is multiplied by row vector with column vector and obtains matrix M4 as row vectork；Solve M4kIt is maximum special
The corresponding feature vector of value indicative, is denoted as w2k, according to step 5.3 same procedure to feature vector w2kCalculate, obtain k-th of evaluation
Block quality degree distribution D under the factork。
6.4 establish quality degree distribution matrix D.Matrix D is by element DklForm, lower label k is meant that evaluation points correspond to
Sequence number, lower label l are meant that block corresponds to sequence number.Matrix kth row are the block quality degree distributions under k-th of evaluation points
Dk, and so on.
Step 6.1 illustrates 1：Block quality degree distribution D under k-th of evaluation pointskIt is a vector, l-th in vector
The numerical value of element is the good and bad degree of corresponding l-th of block.
Step 6.1 illustrates 2：Block contrast matrix M4 under k-th of evaluation pointsk, each matrix element is to pass through block
Compare two-by-two and get.Two block contrasts are taken every time, compare quality quality degree, and the precision of degree is divided into two-stage, first order essence
Degree is upper, middle and lower third gear, corresponding numerical value 9,6,3；If precision is necessary to improve again to the second level, be divided into, it is upper in,
Up and down, it is upper in, in, under, under it is upper and lower in, lower nine gear, correspondence numerical value 9 to 1.If block A is better than block B qualities, journey
Degree is 9 to 1, then block B is 1 to 9 than block A poor qualities, degree, and so on.
Step 6.1 illustrates 3：The comparison of qualitative measure, obtained contrast matrix need to carry out matrix logic consistency check,
Continuous correction matrix passes through until checking, it is consistent to comply with logic.Logical consistency checks deterministic process：If contrast matrix
Maximum eigenvalue is λmax, contrast matrix is n rank matrixes, works as λmax-n<(threshold epsilon is given ε by personnel, value 0<ε<<1), logic
Consistency check passes through.
Step 6.2 illustrates：Frequency is mathematically defined concept.
Step 6.3 illustrates：Min-Max standardization is known method mathematically, and minimum value is noted that when calculating
Value should be slightly smaller than the minimum value of truthful data collection, to prevent 0.
Step 7：Good and bad degree reliability distribution T of the contrast block under each evaluation points is calculated respectively.Wherein, step
Seven include 3 step by step：
7.1 are contrasted two-by-two by block, establish the block quality degree reliability contrast matrix M5 of k-th of evaluation pointsk, under
Label k is meant that the corresponding sequence number of evaluation points；
7.2 solution matrix M5kThe corresponding feature vector of maximum eigenvalue, is denoted as w3k, according to step 5.3 same procedure to spy
Levy vector w3kCalculate, obtain the block quality degree reliability distribution T under k-th of evaluation pointsk。
7.3 establish quality degree reliability distribution matrix T.Matrix T is by element TklForm, lower label k be meant that evaluation because
The corresponding sequence number of son, lower label l are meant that block corresponds to sequence number.Matrix kth row are the block quality degree under k-th of evaluation points
Reliability is distributed Tk, and so on.
Step 7.1 illustrates 1：Good and bad degree reliability refers to the assurance degree to qualitative comparison procedure, or to quantitative data
Source, the assurance degree of computational accuracy.Block quality degree reliability distribution T under k-th of evaluation pointskIt is a vector,
The numerical value of l-th of element is the good and bad degree reliability of corresponding l-th of block in vector.
Step 7.1 illustrates 2：Illustrate 2 same procedures structure M5 according to step 6.1k。
Step 7.1 illustrates 3：Illustrate 3 same procedures to matrix M5 according to step 6.1kMatrix logic consistency check is carried out,
Continuous correction matrix passes through until checking.
Step 8：Calculate relatively preferred index COI, the distribution of block quality degree and the block quality degree reliability of each factor
Distribution is corresponded to according to block to be multiplied, and acquired results are multiplied by the proportion of each evaluation points, then by the result of all evaluation points
Correspond to and add up according to block, that is, obtain COI.
Step 8 illustrates 1：Relatively preferred index (COI) is a data set, by the relatively preferred index structure of each block
Into.The corresponding relatively preferred index of l-th of block, is denoted as COIl.The relatively preferred index of each block can be a numerical value,
Can also be one and the relevant numeric distribution in geographical location, each single item evaluation points for being specifically dependent upon contrast block are by list
A data or a data set represent.COIlCalculation formula such as formula (1)：
COI is denoted as formula (2)：
Wherein m is evaluation points sum；Z is contrast block total number.
Compared with prior art, the present invention what is reached has the beneficial effect that：
1. the present invention is studied on the basis of the existing integrated evaluating method of analysis is of problems, with more governing factor collection
Body difference calculates relatively preferred index, and block overall merit is carried out by exponential number size, establishes a set of dynamic and calculates
Relative evaluation theoretical system, take into account shale gas Enrichment And Reservoiring possibility and exploitability so that result has directive significance.
2. be different from conventional integrated evaluating method, for can quantization factor and the factor that is difficult to quantify use different sides
Method and standard are graded evaluation respectively, and quantitative governing factor and qualitatively governing factor are placed in unified evaluation system by the present invention
Lower calculating, so that more reasonable in same substandard block evaluation result.
3. the present invention considers the reliability of data source, the uncertainty of result of calculation, reliability is made with uncertainty
Into difference bring into relatively preferred index and go to calculate, method system is tighter.
Brief description of the drawings
Fig. 1 is the techniqueflow chart of the present invention；
Fig. 2 is governing factor relation flow graph of the embodiment of the present invention；
Fig. 3 is adjacency matrix M1 data structure diagrams of the embodiment of the present invention.
Embodiment
It is detailed with reference to Fig. 1, Fig. 2, Fig. 3 in order to which technical scheme and beneficial effect is more clearly understood
Illustrate the preferred embodiment of the present invention, it should be noted that specific embodiment described herein only to explain the present invention, and
It is not used in the restriction present invention.
By taking the shale gas block of the river southeast as an example, block W pre-selection well locations have 3 mouthfuls of W1, W2, W3,3 mouthfuls of N1 of block N pre-selection well locations,
N2, N3, block P pre-selection well location 2 mouthfuls of P1, P2, geographical location is different, and 8 mouthfuls of pre-selection well locations of this 3 blocks integrate commenting
Valency, its step process are as shown in Figure 1.
Step 101, on early period geological analysis working foundation, enrichment and the exploitation key element of block W, N, P are collected, and is received
Collect basic data data.
The relevant characterization factor being related to from the aspect of microcosmic, macroscopical, raw storage, exploitation four, is enumerated as follows：Mineral group
Point, it is organic carbon content, porosity, maturity, permeability, amount of coalbed methane generated, fracture development, strata pressure, brittleness, shale thickness, flat
Face spread (area), buried depth, construction.
Step 102, governing factor relation flow graph is established.
Governing factor relation flow graph is shown in Fig. 2.
Step 103, the influence distribution of governing factor in relation flow graph is asked for.
1. establish adjacency matrix M1.Adjacency matrix M1 is shown in Fig. 3.
2. with 0.01 correction matrix M1, frequency distribution matrix is established：Each element of matrix M1 divided by its institute being expert at
There is the sum of element, element of the obtained new value as the frequency distribution matrix M2 positions is as a result as follows：
M2=
[0.004739336,0.004739336,0.004739336,0.004739336,0.004739336,
0.004739336,0.473933649,0.004739336,0.473933649,0.004739336,0.004739336,
0.004739336,0.004739336；0.004739336,0.004739336,0.004739336,0.473933649,
0.004739336,0.473933649,0.004739336,0.004739336,0.004739336,0.004739336,
0.004739336,0.004739336,0.004739336；0.076923077,0.076923077,0.076923077,
0.076923077,0.076923077,0.076923077,0.076923077,0.076923077,0.076923077,
0.076923077,0.076923077,0.076923077,0.076923077；0.008928571,0.008928571,
0.008928571,0.008928571,0.008928571,0.892857143,0.008928571,0.008928571,
0.008928571,0.008928571,0.008928571,0.008928571,0.008928571；0.076923077,
0.076923077,0.076923077,0.076923077,0.076923077,0.076923077,0.076923077,
0.076923077,0.076923077,0.076923077,0.076923077,0.076923077,0.076923077；
0.008928571,0.008928571,0.008928571,0.008928571,0.008928571,0.008928571,
0.008928571,0.892857143,0.008928571,0.008928571,0.008928571,0.008928571,
0.008928571；0.004739336,0.004739336,0.473933649,0.004739336,0.473933649,
0.004739336,0.004739336,0.004739336,0.004739336,0.004739336,0.004739336,
0.004739336,0.004739336；0.008928571,0.008928571,0.008928571,0.008928571,
0.008928571,0.892857143,0.008928571,0.008928571,0.008928571,0.008928571,
0.008928571,0.008928571,0.008928571；0.004739336,0.004739336,0.004739336,
0.004739336,0.473933649,0.004739336,0.473933649,0.004739336,0.004739336,
0.004739336,0.004739336,0.004739336,0.004739336；0.008928571,0.008928571,
0.008928571,0.008928571,0.008928571,0.892857143,0.008928571,0.008928571,
0.008928571,0.008928571,0.008928571,0.008928571,0.008928571；0.008928571,
0.008928571,0.008928571,0.008928571,0.008928571,0.892857143,0.008928571,
0.008928571,0.008928571,0.008928571,0.008928571,0.008928571,0.008928571；
0.004739336,0.004739336,0.004739336,0.473933649,0.004739336,0.004739336,
0.004739336,0.473933649,0.004739336,0.004739336,0.004739336,0.004739336,
0.004739336；0.001968504,0.001968504,0.001968504,0.001968504,0.001968504,
0.001968504,0.196850394,0.196850394,0.001968504,0.196850394,0.196850394,
0.196850394,0.001968504]
3. asking for the corresponding feature vector V0 of maximum eigenvalue 1 using power iteration method, feature vector V0 is set to meet condition：V0
The sum of all vector elements are equal to 1.As a result it is as follows：
V0=
[0.0127,0.0127,0.0267,0.0258,0.0355,0.4022,0.0299,0.3778,0.0187,
0.0152,0.0152,0.0152,0.0127]
Obtain the influence distribution of governing factor：Mineral constituent：0.0127；Organic carbon content：0.0127；Porosity：
0.0267；Maturity：0.0258；Permeability：0.0355；Amount of coalbed methane generated：0.4022；Fracture development：0.0299；Strata pressure：
0.3778；Brittleness：0.0187；Shale thickness：0.0152；Area：0.0152；Buried depth：0.0152；Construction：0.0127.
Step 104, the factor for participating in contrast is extracted in governing factor, according to its corresponding influence distribution values, is established
Evaluation points vector V1.
According to block W, N, P the basic data data obtained, organic carbon content, maturity, strata pressure, shale are chosen
Thickness, buried depth are as a result as follows as evaluation points：
V1=[0.0127,0.0258,0.3778,0.0152,0.0152]
Step 105, the Calculation Estimation factor is than redistribution Wf。
1. matrix M3 is built, it is as a result as follows：
M3=
[1,0.492248062,0.03361567,0.835526316,0.835526316；2.031496063,1,
0.068290101,1.697368421,1.697368421；29.7480315,14.64341085,1,24.85526316,
24.85526316；1.196850394,0.589147287,0.040232927,1,1；1.196850394,0.589147287,
0.040232927,1,1]
2. matrix M3 is changed, it is as a result as follows：
M3=[1,0.5,0.11111,1,1；2,1,0.11111,2,2；9,9,1,9,9；1,0.5,0.11111,1,1；1,
0.5,0.11111,1,1]
3. evaluation points are asked for than redistribution Wf：
The corresponding feature vector w1 of solution matrix M3 maximum eigenvalue.By the w1 Calculation Estimation factors than redistribution Wf.Knot
Fruit is as follows：
Wf=[0.0652,0.1152,0.6892,0.0652,0.0652]
Obtain evaluation points and compare redistribution：Organic carbon content 0.0652, maturity 0.1152, strata pressure 0.6892, page
Rock thickness 0.0652, buried depth 0.0652.
Step 106, good and bad degree distribution D of the contrast block under each evaluation points is calculated respectively.
Organic carbon content, maturity, strata pressure, shale thickness, buried depth have the data of quantization, wherein：
The organic carbon content of W1, W2, W3, N1, N2, N3, P1, P2 is successively：3.2、3.2、3.1、3.4、3.3、3.5、
3.1、3.2；
The maturity of W1, W2, W3, N1, N2, N3, P1, P2 is successively：2.3、2.2、2.3、2.8、2.8、2.7、2.1、
2.0；
The strata pressure of W1, W2, W3, N1, N2, N3, P1, P2 is successively：1.1、1.09、1.1、1.32、1.31、1.30、
0.98、0.97；
The shale thickness of W1, W2, W3, N1, N2, N3, P1, P2 is successively：28、27、28、30、31、31、27、28；
The buried depth of W1, W2, W3, N1, N2, N3, P1, P2 is successively：2652、2822、3429、2690、2811、3530、
2538、2679。
Min-Max standardization is first carried out before comparing, then builds matrix M4, wherein buried depth data all take negative value.
Organic carbon content contrast matrix M41As a result it is as follows：
M41=
[1,1,11,0.355,0.524,0.268,11,1；1,1,11,0.355,0.524,0.268,11,1；0.091,
0.091,1,0.032,0.048,0.024,1,0.091；2.818,2.818,31,1,1.476,0.756,31,2.818；
1.909,1.909,21,0.677,1,0.512,21,1.909；3.727,3.727,41,1.323,1.952,1,41,3.727；
0.091,0.091,1,0.032,0.048,0.024,1,0.091；1,1,11,0.355,0.524,0.268,11,1]
Maturity contrast matrix M42As a result it is as follows：
M42=
[1,1.09,1,0.708,0.708,0.752,1.198,1.33；0.917,1,0.917,0.649,0.649,
0.689,1.099,1.22；1,1.09,1,0.708,0.708,0.752,1.198,1.33；1.413,1.541,1.413,1,1,
1.062,1.693,1.879；1.413,1.541,1.413,1,1,1.062,1.693,1.879；1.331,1.45,1.331,
0.942,0.942,1,1.594,1.769；0.835,0.91,0.835,0.591,0.591,0.627,1,1.11；0.752,
0.82,0.752,0.532,0.532,0.565,0.901,1]
Strata pressure contrast matrix M43As a result it is as follows：
M43=
[1,1.083264,1,0.371608,0.382535,0.394123,12.881188,1301；0.923136,1,
0.923136,0.343045,0.353131,0.363829,11.891089,1201；1,1.083264,1,0.371608,
0.382535,0.394123,12.881188,1301；2.691007,2.915071,2.691007,1,1.029403,
1.060588,34.663366,3501；2.614143,2.831807,2.614143,0.971437,1,1.030294,
33.673267,3401；2.537279,2.748543,2.537279,0.942873,0.970597,1,32.683168,3301；
0.077633,0.084097,0.077633,0.028849,0.029697,0.030597,1,101；0.000769,
0.000833,0.000769,0.000286,0.000294,0.000303,0.009901,1]
Shale thickness contrast matrix M44As a result it is as follows：
M44=
[1,11,1,0.355,0.268,0.268,11,1；0.091,1,0.091,0.032,0.024,0.024,1,
0.091；1,11,1,0.355,0.268,0.268,11,1；2.818,31,2.818,1,0.756,0.756,31,2.818；
3.727,41,3.727,1.323,1,1,41,3.727；3.727,41,3.727,1.323,1,1,41,3.727；0.091,1,
0.091,0.032,0.024,0.024,1,0.091；1,11,1,0.355,0.268,0.268,11,1]
Buried depth contrast matrix M45As a result it is as follows：
M45=
[1,1.23981,8.62512,1.04519,1.22086,976.55556,0.88518,1.03169；0.80658,
1,6.95682,0.84303,0.98472,787.66667,0.71397,0.83214；0.11594,0.14374,1,
0.12118,0.14155,113.22222,0.10263,0.11961；0.95676,1.1862,8.25221,1,1.16808,
934.33333,0.84691,0.98709；0.81909,1.01552,7.06477,0.85611,1,799.88889,
0.72505,0.84505；0.00102,0.00127,0.00883,0.00107,0.00125,1,0.00091,0.00106；
1.12971,1.40062,9.74387,1.18076,1.37922,1103.22222,1,1.16551；0.96928,1.20172,
8.36016,1.01308,1.18336,946.55556,0.85799,1]
By calculating, organic carbon content quality degree distribution D1As a result it is as follows：
D1=[0.086,0.086,0.008,0.242,0.164,0.320,0.008,0.086]
Maturity quality degree is distributed D2As a result it is as follows：
D2=[0.115,0.106,0.115,0.163,0.163,0.154,0.096,0.087]
Strata pressure quality degree is distributed D3As a result it is as follows：
D3=[0.09221719,0.08512899,0.09221719,0.24815707,0.24106890,
0.23398069,
0.00715908,0.00007091]
Shale thickness quality degree is distributed D4As a result it is as follows：
D4=[0.074,0.007,0.074,0.209,0.277,0.277,0.007,0.074]
Buried depth quality degree is distributed D5As a result it is as follows：
D5=[0.1725,0.1391,0.0200,0.1650,0.1413,0.0002,0.1948,0.1672]
Quality degree distribution matrix D is established, it is as a result as follows：
D=
[0.086,0.115,0.09221719,0.074,0.1725；0.086,0.106,0.08512899,0.007,
0.1391；0.008,0.115,0.09221719,0.074,0.02；0.242,0.163,0.24815707,0.209,0.165；
0.164,0.163,0.2410689,0.277,0.1413；0.32,0.154,0.23398069,0.277,0.0002；0.008,
0.096,0.00715908,0.007,0.1948；0.086,0.087,0.00007091,0.074,0.1672]
Step 107：Good and bad degree reliability distribution T of the contrast block under each evaluation points is calculated respectively.
The organic carbon content of block W, N, P, maturity are experimental result, and reliability is basically identical, and three blocks
Strata pressure, shale thickness, buried depth, are established on Use of Geophysical Data processing with basis for interpretation, and the maximum between reliability is poor
Different block W, P of deriving from is two-dimensional seismic survey data, and block N is 3-d seismic exploration data, therefore the reliability of block N is more
It is high.The division for comparing precision uses upper, middle and lower third gear, is extra fine grade.Reliability contrast matrix is established as follows：
Organic carbon content reliability contrast matrix M51：
M51=
[1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,
1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1]
Maturity reliability contrast matrix M52：
M52=
[1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,
1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1；1,1,1,1,1,1,1,1]
Strata pressure reliability contrast matrix M53：
M53=
[1,1,1,0.333,0.333,0.333,1,1；1,1,1,0.333,0.333,0.333,1,1；1,1,1,0.333,
0.333,0.333,1,1；3,3,3,1,1,1,3,3；3,3,3,1,1,1,3,3；3,3,3,1,1,1,3,3；1,1,1,0.333,
0.333,0.333,1,1；1,1,1,0.333,0.333,0.333,1,1]
Shale thickness reliability contrast matrix M54：
M54=
[1,1,1,0.333,0.333,0.333,1,1；1,1,1,0.333,0.333,0.333,1,1；1,1,1,0.333,
0.333,0.333,1,1；3,3,3,1,1,1,3,3；3,3,3,1,1,1,3,3；3,3,3,1,1,1,3,3；1,1,1,0.333,
0.333,0.333,1,1；1,1,1,0.333,0.333,0.333,1,1]
Buried depth reliability contrast matrix M55：
M55=
[1,1,1,0.333,0.333,0.333,1,1；1,1,1,0.333,0.333,0.333,1,1；1,1,1,0.333,
0.333,0.333,1,1；3,3,3,1,1,1,3,3；3,3,3,1,1,1,3,3；3,3,3,1,1,1,3,3；1,1,1,0.333,
0.333,0.333,1,1；1,1,1,0.333,0.333,0.333,1,1]
Given threshold ε is 0.1, and 5 reliability contrast matrixes of the above pass through logical consistency inspection.By calculating, have
Machine carbon content reliability is distributed T1：
T1=[0.125,0.125,0.125,0.125,0.125,0.125,0.125,0.125]
Maturity reliability is distributed T2：
T2=[0.125,0.125,0.125,0.125,0.125,0.125,0.125,0.125]
Strata pressure reliability is distributed T3：
T3=[0.0714,0.0714,0.0714,0.2143,0.2143,0.2143,0.0714,0.0714]
Shale thickness reliability is distributed T4：
T4=[0.0714,0.0714,0.0714,0.2143,0.2143,0.2143,0.0714,0.0714]
Buried depth reliability is distributed T5：
T5=[0.0714,0.0714,0.0714,0.2143,0.2143,0.2143,0.0714,0.0714]
Establish reliability distribution matrix T：
T=
[0.125,0.125,0.0714,0.0714,0.0714；0.125,0.125,0.0714,0.0714,0.0714；
0.125,0.125,0.0714,0.0714,0.0714；0.125,0.125,0.2143,0.2143,0.2143；0.125,
0.125,0.2143,0.2143,0.2143；0.125,0.125,0.2143,0.2143,0.2143；0.125,0.125,
0.0714,0.0714,0.0714；0.125,0.125,0.0714,0.0714,0.0714]
Step 108：According to formula (1) and (2), relatively preferred index COI is calculated：
Wherein, the relatively preferred index of W1, W2, W3, N1, N2, N3, P1, P2 are successively：0.0080、0.0071、
0.0067、0.0462、0.0451、0.0433、0.0027、0.0031。
It is arranged in order according to relatively preferred exponential size, is sequentially：N1、N2、N3、W1、W2、W3、P2、P1.On the whole,
Block N is that more preferably Favorable Areas, the geographical location where N1 are relatively optimal pre-selection well locations relatively.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all originals in the present invention
Then with all any modification, equivalent and improvement made within spirit etc., it is included within protection scope of the present invention.
Unspecified is the prior art.
Claims (10)
- A kind of 1. shale gas block exploitation potential assessment method based on relatively preferred index, it is characterised in that including in detail below Step：Step 1: collecting the Enrichment And Reservoiring and exploitation key element of shale gas research block, basic data data are collected；Step 2: establish governing factor relation flow graph；Step 3: ask for the influence distribution of governing factor；Step 4: establish evaluation points vector；Step 5: the Calculation Estimation factor compares redistribution；Step 6: good and bad degree distribution of the contrast block under each evaluation points is calculated respectively；Step 7: good and bad degree reliability distribution of the contrast block under each evaluation points is calculated respectively；Step 8: calculate relatively preferred index COI.
- 2. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 1, its It is characterized in that：In the step 1, the Enrichment And Reservoiring and exploitation key element of collecting shale gas research block are established in geology point early period Analyse on working foundation, source includes：Hydrocarbon generation capacity, reservoir storage and collection performance, gas reservoir cap rock condition and/or easy exploitation property；Collect Basic data data include：Physical prospecting, drilling well, well logging and/or geologic information；In the step 2, governing factor relation flow graph is established according to the influence relation between factor；In the step 3, the corresponding adjacency matrix of relation flow graph is initially set up, then between 0 to 1 and leveling off to 0 Decimal carry out 0 value in correction matrix, establish frequency distribution matrix, pass through the influence point that power iteration method calculates governing factor afterwards Cloth；The step 4, evaluation points vector method for building up are：The factor for participating in contrast is extracted in governing factor as evaluation The factor, vector element are made of successively corresponding influence distribution values；In the step 5, comparator matrix is initially set up, then changes matrix, afterwards solution matrix feature vector, to feature vector Converted to obtain evaluation points proportion distribution vector.
- 3. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 2, its It is characterized in that：Frequency distribution matrix establishment method is：Matrix after correcting 0 value, by each of which element divided by the element institute The sum of all elements being expert at, element of the obtained new value as same position in frequency distribution matrix.
- 4. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 2, its It is characterized in that：Comparator matrix method for building up is：It regard evaluation points vector as column vector, the composition reciprocal of each element of vector Vector is used as row vector, and being multiplied by row vector with column vector obtains matrix；Changing the method for comparator matrix is：The element for being more than 9 in matrix is replaced with 9, the element between 1 and 9 rounds up； Change the element that matrix element is less than 1：If aijIt is the element in matrix, lower label i, j is be expert at and column here, if aij<1, then its value is revised as 1/aji；The conversion carried out to feature vector refers to：By the sum of each element of feature vector divided by all elements, obtained new value is made For the element numerical value of same position in evaluation points proportion distribution vector.
- 5. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 1, its It is characterized in that：In the step 6, the block quality degree distribution under each evaluation points is a vector；Solution procedure needs It is qualitative or quantitative to judge the Evaluation: Current factor；If evaluation points can only qualitative measure, compared two-by-two by block, built The block contrast matrix of the factor is found, the corresponding feature vector of solution matrix maximum eigenvalue, converts feature vector, obtain Block quality degree distribution under to the factor；If evaluation points can be with quantitative measurement, and is characterized by frequency, then excellent The numerical value of the bad degree each element of distribution vector is the sum of current frequency divided by all frequencies；Spent if evaluation points can quantify Amount, and characterized by property value size, then Min-Max standardization is first carried out, then block contrast matrix is built, solve square The corresponding feature vector of battle array maximum eigenvalue, converts feature vector, obtains the block quality degree distribution under the factor, right The method that feature vector converts is consistent with the conversion content described in claim 4.
- 6. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 5, its It is characterized in that：Under qualitative measure, block compares two-by-two, and the contrast matrix method of foundation is as follows：Two block contrasts are taken every time, than Compared with quality quality degree, the precision of degree is divided into two-stage, and the first class precision is upper, middle and lower third gear, corresponding numerical value 9,6,3；If Precision is necessary to improve again to the second level, then be divided into, it is upper in, up and down, in it is upper, in, under, under it is upper and lower in, lower nine Gear, corresponding numerical value 9 to 1.If block A is better than block B qualities, degree is 9 to 1, then block B is than block A poor qualities, degree It is 1 to 9, and so on.
- 7. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 6, its It is characterized in that：The comparison of qualitative measure, obtained comparator matrix need to carry out matrix logic consistency check, continuous correction matrix Pass through until checking, it is consistent to comply with logic.Logical consistency checks that deterministic process is as follows：If the maximum feature of comparator matrix It is worth for λmax, comparator matrix is n rank matrixes, works as λmaxAnd the difference of n is less than given minimum, then logical consistency inspection passes through.
- 8. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 1, its It is characterized in that：In the step 7, contrasted two-by-two by block first, establish the block quality degree reliability of each evaluation points Contrast matrix；The corresponding feature vector of each matrix maximum eigenvalue is solved again, is converted to feature vector, is obtained result； Good and bad degree reliability refers to the assurance degree to qualitative comparison procedure, or the assurance in the source, computational accuracy to quantitative data Degree.
- 9. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 8, its It is characterized in that：Block quality degree reliability contrast matrix establishment method and the content one described in claim 6 of each evaluation points Cause.Matrix logic consistency check is consistent with content described in claim 7.The method to convert to feature vector will with right Ask the conversion content described in 2 consistent.
- 10. a kind of shale gas block exploitation potential assessment method based on relatively preferred index according to claim 1, its It is characterized in that：In the step 8, calculating the method for relatively preferred index COI is：The block quality degree distribution of each factor with The distribution of block quality degree reliability is corresponded to according to block to be multiplied, and acquired results are multiplied by the proportion of each evaluation points, then by institute The result for having evaluation points is corresponded to according to block to add up, that is, obtains COI.
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