CN108333626B - A kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy - Google Patents
A kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy Download PDFInfo
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- CN108333626B CN108333626B CN201810021231.9A CN201810021231A CN108333626B CN 108333626 B CN108333626 B CN 108333626B CN 201810021231 A CN201810021231 A CN 201810021231A CN 108333626 B CN108333626 B CN 108333626B
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- 230000002068 genetic effect Effects 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000014759 maintenance of location Effects 0.000 title claims abstract description 16
- 238000010353 genetic engineering Methods 0.000 claims abstract description 7
- 230000035772 mutation Effects 0.000 claims abstract description 7
- 230000003044 adaptive effect Effects 0.000 claims abstract description 6
- 230000008569 process Effects 0.000 claims abstract description 4
- 108090000623 proteins and genes Proteins 0.000 claims description 4
- 230000003595 spectral effect Effects 0.000 claims description 4
- 238000001228 spectrum Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000006978 adaptation Effects 0.000 claims description 2
- 230000010429 evolutionary process Effects 0.000 claims description 2
- 238000000605 extraction Methods 0.000 claims 2
- 230000002028 premature Effects 0.000 abstract description 4
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- 230000000452 restraining effect Effects 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/622—Velocity, density or impedance
- G01V2210/6226—Impedance
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Abstract
A kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy, belong to Geophysics Inversion field, especially with regard to the wave impedance inversion technique in oil geophysical exploration, it is intended to provide a kind of improved adaptive GA-IAGA Optimum Impedance Inversion Method, for solving premature problem of the standard genetic algorithm in wave impedance inversion, so that inversion result is relatively reliable, mainly include the following steps: the objective function that wave impedance inversion is 1. constructed according to convolution model；2. the estimation of seismic wavelet by homomorphic theory；3. being encoded using binary coding mode to wave impedance；4. calculating the fitness value of each individual with objective function, and quantitatively evaluating is carried out to individual according to this；5. generating population of new generation according to the selection mode of best retention strategy；6. carrying out genetic manipulation according to the intersection of design, mutation operator；7. idiotype is converted to phenotype according to corresponding decoding process and realizes that algorithm recycles；8. seeking wave impedance using recurrence method.
Description
Technical field
The present invention provides a kind of genetic algorithm Optimum Impedance Inversion Methods based on best retention strategy, belong to geophysics
It is calculated especially with regard to the wave impedance inversion technique in oil geophysical exploration for solving standard genetic in inverting field
Premature problem of the method in wave impedance inversion.
Background technique
There are the weakness that Premature Convergence and convergence rate are slow, current improved methods in practical application for standard genetic algorithm
Mostly for the macrotechnique of population, genetic manipulation, genetic operator improvement and parallelization operation etc..In coding mode,
Dynamic coding mode, floating-point encoding mode, Gray code mode etc., in terms of the macrotechnique of population, Yao Wei powder are developed
(2015) propose dynamic microhabitat coevolution model, and in terms of the improvement of selection operator, Zhang Jing (2015) is proposed
Adaptive sequencing selection mode, in terms of crossover operator improvement, Davis (1991) proposes serial number crossover operator and uniformly row
Sequence crossover operator, in terms of the improvement of mutation operator, Liu Li (2015) proposes gene position TSP question genetic operator, on
The search performance that innovatory algorithm improves genetic algorithm to varying degrees is stated, but is directed to the particular problem of wave impedance inversion or more
Compared to standard genetic algorithm, implementation process is cumbersome for corrective measure, poor for different problem adaptability, in terms of convergence not
Clear superiority can be embodied.The present invention sets about from selection operator, proposes a kind of genetic algorithm based on optimal selection strategy, can have
Effect overcomes the problems, such as the premature problem in wave impedance inversion, and adaptability is good, easy to accomplish.
Summary of the invention
The present invention is intended to provide a kind of overcome standard genetic algorithm to lose in the improvement of wave impedance inversion mid-early maturity convergence problem
Propagation algorithm, it is to guarantee that other genetic operators are constant on the basis of standard genetic algorithm, roulette wheel selection mode is abandoned, using one
The best retention strategy selection mode of kind.
Specific steps of the invention include:
(1) initialization operation, setting control parameter and generation initial population, and calculate the fitness value of population.
(2) individual in parent population is ranked up by fitness value size, seeks the average fitness value of population, will fits
The individual that should be worth greater than average fitness value is genetic directly in next-generation population.
(3) using highest fitness value as template, fitness value makees cross-correlation judgement with the individual with highest fitness, will
Fitness value is high and the biggish individual of difference in correlation forms new population.
(4) according to principle in (3), gradually with the high individual of fitness value for template, the individual composition of different templates is selected
New population.
(5) judge whether to reach population scale, if it is, carrying out the genetic manipulations such as next step intersection, variation, otherwise will
The individual of removal sequentially supplies the scarce quantity of population institute by fitness value size, until reaching population scale.
The present invention is a kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy, is had a characteristic that
(1) genetic algorithm based on best retention strategy takes a kind of be based on by the sequence of individual adaptation degree size, mutually
The selection mode of the operations such as pass, selection ensure that in each evolutionary process, filial generation can retain the optimized individual in parent,
The diversity and intersection, the stability of mutation operation for guaranteeing population gene are avoided and are lost based on the standard under roulette wheel selection mode
The precocious phenomenon that propagation algorithm generates, makes algorithm that may finally search globally optimal solution.
(2) compared to other Revised genetic algorithums, realize that simply algorithm stability is good for wave impedance inversion problem,
Calculating speed is fast.
Detailed description of the invention
Fig. 1 and Fig. 2 is respectively the single-channel seismic record of standard genetic algorithm and improved adaptive GA-IAGA inverting, from inversion result
On see, Fig. 1 be standard genetic algorithm iteration 11 times restrain obtain inverting record, with original record related coefficient be 94.4%, partially
Difference is larger；Fig. 2 is the improved adaptive GA-IAGA iteration 32 times inverting records for restraining to obtain, and is with original seismic data related coefficient
99.6%, the wave impedance and actual well drilled that recurrence method acquires are coincide.It theoretically analyzes, standard genetic algorithm is due to using roulette wheel
Selection mode generates higher fitness individual x at evolution initial stage, and other individuals are eliminated rapidly, most of individual and x phase
Together, intersected, the individual of mutation operation is in a disadvantageous position in competition, is easy to be eliminated, all in initial stage population of evolving
Individual falls into same extreme value and stops evolving.And improved adaptive GA-IAGA passes through by the sequence of fitness size, cross-correlation judgement, template
The operation such as selection improves the diversity of population gene, ensure that subsequent intersection, variation under the premise of guaranteeing population's fitness
The stability of operation, may finally search globally optimal solution, and inversion accuracy is higher.
Specific embodiment
A kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy, specific implementation step are as follows:
(1) objective function is constructed
The objective function of wave impedance inversion is constructed according to convolution model:
In formula, D is real seismic record, and W (t) is seismic wavelet, and Z is wave impedance, and R is reflection coefficient, and N is reflection coefficient
Sequence length, Δ t are the sampling interval.
Construct wave impedance recursive function:
R is reflection coefficient in formula, and Z is wave impedance.
(2) the estimation of seismic wavelet by homomorphic theory, by reflection coefficient sequence intermediary heat spectrum and earthquake in intermediary heat spectral domain
The intermediary heat spectrum of wave separates, and then obtains the intermediary heat spectral sequence of seismic wavelet, is transformed to time-domain then to get then
Between domain seismic wavelet.
(3) wave impedance is encoded using binary coding mode, determines the genotype X of individual.
(4) fitness value of each individual and the average fitness of population are calculated with the objective function that formula (1) constructs
Value, and quantitatively evaluating is carried out to individual according to this.
(5) population of new generation is generated according to the selection mode of best retention strategy.
(6) genetic manipulation is carried out according to the intersection of design, mutation operator.
(7) idiotype is converted to phenotype and substitutes into termination condition according to corresponding decoding process and judged,
Subsequent genetic manipulation is terminated if meeting termination condition, otherwise returns to (4) step.
(8) wave impedance is asked using recurrence method.
Claims (5)
1. a kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy, it is characterised in that foring a set of completely newly has
The Optimum Impedance Inversion Method of effect, such as following steps:
(1) objective function of wave impedance inversion is constructed according to convolution model:
In formula, D is real seismic record, and W (t) is seismic wavelet, and i is sampling number, ZiFor the wave impedance at ith sample point,
N is reflection coefficient sequence length, and Δ t is sampling interval, tiIt is ith sample point when walking, δ (ti- i Δ t) is using i as variable
Dirac function, that is, meet
Construct wave impedance recursive function:
R in formulaiFor the reflection coefficient at ith sample point, ZiFor the wave impedance at ith sample point；
(2) the estimation of seismic wavelet by homomorphic theory, by reflection coefficient sequence intermediary heat spectrum and seismic wavelet in intermediary heat spectral domain
Intermediary heat spectrum separates, and then obtains the intermediary heat spectral sequence of seismic wavelet, and wavelet is separated from seismic data, then will
It transforms to time-domain to get time-domain seismic wavelet is arrived；
(3) initialization operation, setting control parameter and generation initial population, and calculate the fitness value of population；
(4) individual in parent population is ranked up by fitness value size, the average fitness value of population is sought, by adaptive value
Individual greater than average fitness value is genetic directly in next-generation population；
(5) using highest fitness value as template, fitness value makees cross-correlation judgement with the individual with highest fitness, will adapt to
Angle value is high and the biggish individual of difference in correlation forms new population；
(6) according to principle in (5), gradually the individual of different templates is selected to form newly for template with the high individual of fitness value
Population；
(7) judge whether to reach population scale, if it is, next step intersection, mutation operation are carried out, otherwise by the individual of removal
The scarce quantity of population institute is sequentially supplied by fitness value size, until reaching population scale；
(8) genetic manipulation is carried out according to the intersection of design, mutation operator；
(9) idiotype is converted to phenotype and substitutes into termination condition according to corresponding decoding process and judged, if
Meet termination condition and then terminate subsequent genetic manipulation, otherwise returns to (4) step；
(10) wave impedance is asked using recurrence method.
2. a kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy according to claim 1, feature
Be: the objective function established based on convolution model is compared to the objective function that the wave equation based on wave theory is established
It is strong with noiseproof feature, the characteristics of algorithmic stability.
3. a kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy according to claim 1, feature
Be: wavelet extraction method is not by borehole restraint, and the wavelet precision of extraction is higher, and fitting effect is good.
4. a kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy according to claim 1, feature
Be: the recurrence method inverting wave impedance of use has well without can use under the conditions of well, few suitable for exploration initial stage Wu Jing and well
Situation.
5. a kind of genetic algorithm Optimum Impedance Inversion Method based on best retention strategy according to claim 1, feature
It is: based on the best retention strategy selection mode by operations such as the sequence of individual adaptation degree size, cross-correlation, selections, each
In secondary evolutionary process, filial generation always remains individual best in parent, ensure that the diversity and intersection, variation of population gene
The stability of operation can finally search globally optimal solution.
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| CN1710446A (en) * | 2005-06-21 | 2005-12-21 | 中国石油大学(北京) | Method for inversion constituting virtual well data using before-folded seismic wave form |
| CN104977609A (en) * | 2014-04-11 | 2015-10-14 | 中国石油集团东方地球物理勘探有限责任公司 | Prestack longitudinal wave and transverse wave combined inversion method based on rapid simulated annealing |
| CN105445791A (en) * | 2015-11-25 | 2016-03-30 | 成都理工大学 | Stratum aperture pressure prediction method based on variety earthquake attributes |
| CN107462924A (en) * | 2017-07-27 | 2017-12-12 | 西安交通大学 | A kind of absolute wave impedance inversion method independent of well-log information |
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| US7148683B2 (en) * | 2001-10-25 | 2006-12-12 | Intematix Corporation | Detection with evanescent wave probe |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1710446A (en) * | 2005-06-21 | 2005-12-21 | 中国石油大学(北京) | Method for inversion constituting virtual well data using before-folded seismic wave form |
| CN104977609A (en) * | 2014-04-11 | 2015-10-14 | 中国石油集团东方地球物理勘探有限责任公司 | Prestack longitudinal wave and transverse wave combined inversion method based on rapid simulated annealing |
| CN105445791A (en) * | 2015-11-25 | 2016-03-30 | 成都理工大学 | Stratum aperture pressure prediction method based on variety earthquake attributes |
| CN107462924A (en) * | 2017-07-27 | 2017-12-12 | 西安交通大学 | A kind of absolute wave impedance inversion method independent of well-log information |
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