CN109164485A - A kind of quantitative analysis method influencing low order fault accuracy of identification - Google Patents
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Abstract
The invention discloses a kind of quantitative analysis methods for influencing low order fault accuracy of identification, on the basis of analysing in depth low order fault geology characteristic and seismic response features, for the influence factor of low order fault identification, design low order fault geological model, main feature of the low order fault in seismic data is had studied by seismic forward simulation, by the seismic response features for analyzing different stage tomography, induction and conclusion goes out the fault recognizing template of different earthquake wavelet dominant frequency, the fault recognizing template of the noise containing different proportion, the fault recognizing template at different section inclination angle, the fault recognizing template at Different Strata inclination angle, the fault recognizing template of section dip angle and stratigraphic dip, conventional data and the tomography resolving power of high-precision data identify template under different depth, common seismic data and high precision seismic data fault throw resolution ratio power with Depth intersects resultant curve comparison diagram, and fault throw resolving power and depth relationship template table are calculated by fitting formula, so as to form the quantitative analysis method of the influence low order fault accuracy of identification of complete set, reliable foundation and its directive function are provided for the identification and explanation of low order fault.
Description
Technical field
The present invention relates to the exploration and development field of low order fault seismic recognition, especially relate to a kind of influence low sequence grade
The quantitative analysis method of fault recognizing precision.
Background technique
With the continuous improvement of In Oil Field Exploration And Development degree, the status of fault block type oil-gas reservoir is more and more important, therein low
Sequence grade tomography is paid more and more attention, because structure detail has been transformed in it, is controlled oil water relation and remaining oil distribution, is seriously affected
The application of oil reservoir development technology, thus this low order fault becomes that In Oil Field Exploration And Development cannot be avoided and that does not walk around asks
Topic, it is necessary to which development is targetedly studied.
It is complete disconnected other than being compared between doing well using drilling data identification breakpoint in terms of low order fault research
Layer and fracture system research still will rely on three dimensional seismic data and corresponding interpretation technique.Since the level of low order fault is disconnected
Away from and normal throw all very littles, generally only 5-10m is even more small, thus is difficult on seismic profile to have apparent lineups wrong
Disconnected feature, usually only micro- even micro- twisting of bad break are easy to that local structure is taken as to change in general structure interpretation
And be ignored, thus special interpretation technique is needed to extract and strengthen the seismic signature of craven fault, it obtains about the clear of tomography
Clear and intuitive image avoids because explaining result irrationality caused by personnel's experience.
The problem that low order fault identification at present faces mainly has:
(1) low order fault identification difficulty is larger, because its heave and normal throw are all smaller, on seismic profile
It is difficult have apparent lineups bad break feature；
(2) factor for influencing low order fault identification is more, seismic data, different depth, the friction speed knot of different accuracy
The factors such as structure, different noises, Different Strata inclination angle, different co-hades have much influences unclear low order fault identification；
(3) combining form of the low order fault on section is various, plane combination mode multi-solution is strong, how reasonably to break
Split the problem in system in combination and low order fault explanation.
In terms of the analysis of Influential Factors of craven fault identification, existing documents and materials are mainly by establishing the forward modeling of all-wave field
Geological model, on dominant frequency, the velocity error, lateral resolution, free earth's surface for influencing geological structure identification during acquisition process
Etc. factors inquired into, can in seismic prospecting acquisition and processing parameter beneficial reference be provided.It is related to the present invention
In existing literature data and application technology, still not for influencing the quantitative analysis method of low order fault accuracy of identification, thus
The guidance of effect can not be provided with for the seismic recognition of low order fault and explanation.
Summary of the invention
The invention aims to the Research Challenges for low order fault identification, provide a kind of influence low order fault knowledge
The quantitative analysis method of other precision provides reliable foundation and its directive function for the identification and explanation of low order fault.
In order to achieve the above objectives, the present invention is implemented according to following technical scheme:
A kind of quantitative analysis method influencing low order fault accuracy of identification, comprising the following steps:
Step 1, disconnected for low sequence grade on the basis of analysing in depth low order fault geology characteristic and seismic response features
The influence factor of layer identification, designs low order fault geological model；
Step 2, by seismic forward simulation, main feature of the low order fault in seismic data is studied；
Step 3, carry out the impact analysis to low order fault accuracy of identification, the tomography under induction and conclusion different affecting factors
Identification template, fault throw resolution ratio power intersect resultant curve and its template table with depth.
In step 1, low order fault geology characteristic is as follows: if (1) bed boundary and seismic reflection continuity are preferable,
It is unobvious that it shows as fault feature, it is difficult to identify；If interface and reflection continuity are poor, bifurcated, merging, disconnection phenomenon are tight
Weight, it appears that everywhere can hiatal fault, be equally difficult to；(2) tomography on section combining form multiplicity, and signal distributions from
It dissipates, influences each other, so that fault interpretation is difficult.
Therefore, during carrying out the analysis of Influential Factors of low order fault accuracy of identification, low order fault knowledge is being carried out
During the analysis of Influential Factors of other precision, it is directed to buried depth, velocity structure, dominant frequency of seismic wavelet, signal-to-noise ratio, section respectively
Inclination angle, attitude of stratum, stratum and section angle influence the factor of low order fault accuracy of identification, design different types of low sequence
Grade tomography geological model.
Specifically, the low order fault geological model designed in step 2 for step 1, by simulating field inspection system
System determines the position of excitation point and receiving point, simulates epicenter excitation, obtains common-source point earthquake record, then obtains to simulation
Common-source point earthquake record carries out pre-stack depth migration imaging, finally obtains the seismic response of given geological model as a result, analysis is disconnected
The seismic response features of layer model provide foundation for the identification and explanation of tomography.
It specifically, is by the Seismic forward mould to the low order fault geological model designed in step 1 in step 3
It is quasi-, main feature of the low order fault in seismic data is had studied, through induction and conclusion, has respectively obtained different earthquake wavelet master
Fault recognizing template, the fault recognizing template at different section inclination angle, difference of the fault recognizing template of frequency, the noise containing different proportion
Under the fault recognizing template of stratigraphic dip, the fault recognizing template of section dip angle and stratigraphic dip, different depth conventional data with
The tomography resolving power identification template of high-precision data, common seismic data and high precision seismic data fault throw resolution ratio power with
Depth intersects resultant curve comparison diagram, obtains fault resolution power with the functional relation of change in depth by least square fitting,
And fault throw resolving power and depth relationship template table are calculated, it is that the identification of actual seismic data low order fault is conciliate
Offer guidance is provided.
Compared with prior art, the invention has the benefit that
The quantitative analysis method of influence low order fault accuracy of identification in the present invention is with having fully considered low order fault
Matter feature has studied main feature of the low order fault in seismic data by seismic forward simulation, disconnected to low sequence grade is influenced
The factors of layer accuracy of identification such as buried depth, velocity structure, dominant frequency of seismic wavelet, signal-to-noise ratio, section dip angle, stratum produce
Analysis and research have been carried out in shape and stratum and the angle of section etc., and induction and conclusion has gone out the tomography of different earthquake wavelet dominant frequency
Identify template, the fault recognizing template of the noise containing different proportion, the fault recognizing template at different section inclination angle, Different Strata inclination angle
Fault recognizing template, the fault recognizing template of section dip angle and stratigraphic dip, conventional data and high-precision provide under different depth
Tomography resolving power identification template, the common seismic data of material are intersected with high precision seismic data fault throw resolution ratio power with depth
Resultant curve comparison diagram, and fault throw resolving power and depth relationship template table are calculated by fitting formula, for practically
The identification and explanation of shake data low order fault provide reliable foundation and its directive function.Therefore, method of the invention tool
There are good application effect and promotion prospect.
Detailed description of the invention
Fig. 1 is the flow chart for the quantitative analysis method that the present invention influences low order fault accuracy of identification.
Fig. 2 a is shallow-layer (1000-1500m) geological model；Fig. 2 b is middle-shallow layer (1500-2000m) geological model；Fig. 2 c
It is mid-deep strata (2000-2500m) geological model；Fig. 2 d is deep layer (2800-3300m) geological model.
Fig. 3 a is the seismic forward simulation section of shallow-layer (1000-1500m) geological model；Fig. 3 b middle-shallow layer (1500-
2000m) the seismic forward simulation section of geological model；Fig. 3 c is the Seismic forward mould of mid-deep strata (2000-2500m) geological model
Quasi- section；Fig. 3 d is the seismic forward simulation section of deep layer (2800-3300m) geological model.
Fig. 4 is the fault recognizing template of different earthquake wavelet dominant frequency.
Fig. 5 is the fault recognizing template of the noise containing different proportion.
Fig. 6 is the tomography resolving power template of conventional data and high-precision data under different depth.
Fig. 7 be conventional data, high-precision data fault throw resolution ratio power intersect composite curve chart with depth.
Fig. 8 is the geological model of different co-hades.
Fig. 9 is the forward simulation section of different co-hades.
Figure 10 is the fault recognizing template of different co-hades.
Figure 11 a is the positive tomography geological model that depth of stratum is incremented by the geological model with Different Strata inclination angle；11b is
Depth of stratum is incremented by the forward simulation section of the geological model with Different Strata inclination angle.
Figure 12 a is that depth of stratum successively decreases the antithetic faults geological model of the geological model with Different Strata inclination angle；12b is
Depth of stratum successively decreases the forward simulation section of the geological model with Different Strata inclination angle.
Figure 13 a is the recognition template of Different Strata inclination angle forward direction normal fault；Figure 13 b is Different Strata reversal of dip normal fault
Recognition template.
Figure 14 is the fault recognizing module of section dip angle and stratigraphic dip.
Figure 15 is the weight of the various influence factors of fault recognizing.
Specific embodiment
The invention will be further described combined with specific embodiments below, in the illustrative examples and explanation of the invention
For explaining the present invention, but it is not as a limitation of the invention.
As shown in Figure 1, a kind of quantitative analysis method of influence low order fault accuracy of identification of the invention, including following step
It is rapid:
Step 1, disconnected for low sequence grade on the basis of analysing in depth low order fault geology characteristic and seismic response features
The influence factor of layer identification, designs low order fault geological model:
Low order fault geology characteristic is as follows: if (1) bed boundary and seismic reflection continuity are preferable, showing as breaking
Layer feature is unobvious, it is difficult to identify；If interface and reflection continuity are poor, bifurcated, merging, disconnection phenomenon are serious, it appears that with
Place can hiatal fault, be equally difficult to；(2) combining form multiplicity of the tomography on section, and signal distributions are discrete, mutual shadow
It rings, so that fault interpretation is difficult.
Therefore, during carrying out the analysis of Influential Factors of low order fault accuracy of identification, low order fault knowledge is being carried out
During the analysis of Influential Factors of other precision, it is directed to buried depth, velocity structure, dominant frequency of seismic wavelet, signal-to-noise ratio, section respectively
Inclination angle, attitude of stratum, stratum and section angle influence the factor of low order fault accuracy of identification, devise the low sequence of following a few classes
Grade tomography geological model, specific as follows:
(1) it devises and respectively represents shallow-layer (1000-1500m), middle-shallow layer (1500-2000m), mid-deep strata (2000-
2500m), the geological model of four kinds of friction speed structures of deep layer (2800-3300m)；
(2) dominant frequency of seismic wavelet separately designs as 20Hz, 25Hz, 30Hz, 35Hz, 40Hz, 45Hz, 50Hz；
(3) noise-containing ratio is respectively 5%, 10%, 15%, 20%, 25%, 30%, 50%；
(4) section dip angle is respectively 90 °, 85 °, 80 °, 70 °, 60 °, 50 °, 40 °, 30 °, 20 °；
(5) having separately designed section dip angle is two distinct types of attitude of stratum model in the case where 70 °: depth of stratum
It is sequentially reduced, positive normal fault model when stratigraphic dip is sequentially increased；Depth of stratum is sequentially increased, stratigraphic dip is sequentially increased
When Antithetic normal fault model.
Step 2, by seismic forward simulation, main feature of the low order fault in seismic data is studied: specifically, needle
The position of excitation point and receiving point is determined by simulating field layout to the low order fault geological model that step 1 designs
It sets, simulates epicenter excitation, obtain common-source point earthquake record, prestack depth then is carried out to the common-source point earthquake record that simulation obtains
Migration imaging finally obtains the seismic response of given geological model as a result, analyzing the seismic response features of FAULT MODEL, is tomography
Identification and explain provide foundation；
Wherein, the Seismic Pre-stack Forward Modeling process based on one-way wave operator is as follows:
Assuming that receiving plane is horizontal, the formation of total big gun collection record is illustrated by taking two dimension as an example.The source wavefield of frequency domain and inspection
Wave resonance wave field is denoted as P (x respectively0,z0；ω) and G (xG,z0；ω), surface seismic records and reflection coefficient are denoted as SP (x, z=respectively
0；And R (x, z) t), the specific steps are as follows:
1. matter model net is formatted, and calculates the reflection R (x in respective nodesj,zi)。
2. R (x, z) is extended to frequency invariant function R ' (x, z；ωn):
R (x, z)=R ' (x, z；ωn)；N=1,2 ..., N；N=int (ωmax/Δω)
3. by P (x0,z0；ω) and G (xG,z0；ω) continuation obtains P (x, z separately downi+1；ω) and G (x, zi+1；ω).
4. calculating depth zi+1The new focus P generated0(x,zi+1；ω), it may be assumed that
P0(x,zi+1；ω)=P (x, zi+1；ω)×R(x,zi+1；ω)
5. calculating depth zi+1The reflecting interface at place forward record P (x, z generatedi+1；ω):
P(x,zi+1；ω)=G (x, zi+1；ω)×P0(x,zi+1；ω)
6. carrying out lateral stacking, entire depth z is soughti+1The possible reflection in place is remembered in the earthquake of fixed geophone station
Record PG(xG,zi+1；ω):
7. 4. repeating step arrives the P for 6. obtaining all depthsG。
8. carrying out longitudinal superposition, current geophone station is obtained in the earthquake record P (x of frequency domainG, ω):
L=int (zmax/Δz)
Inverse-Fourier transform is carried out to above formula, obtains the earthquake record P (x of time-domainG,t)。
9. change geophone station coordinate, repeat step 3. -8., obtain current shot point completely altogether big gun collection earthquake record.
10. change current shot position, repeat step 3. -9., until obtain all be total to big gun collection earthquake records
Step 3, carry out the impact analysis to low order fault accuracy of identification, the tomography under induction and conclusion different affecting factors
Identification template, fault throw resolution ratio power intersect resultant curve and its template table with depth:
Specifically being had studied low by the seismic forward simulation to the low order fault geological model designed in step 1
Main feature of the sequence grade tomography in seismic data, through induction and conclusion, the tomography for having respectively obtained different earthquake wavelet dominant frequency is known
Other template, the fault recognizing template of the noise containing different proportion, the fault recognizing template at different section inclination angle, Different Strata inclination angle
Conventional data and high-precision data under the fault recognizing template of fault recognizing template, section dip angle and stratigraphic dip, different depth
Tomography resolving power identification template, common seismic data intersected with high precision seismic data fault throw resolution ratio power with depth it is comprehensive
Curve comparison figure is closed, fault resolution power is obtained with the functional relation of change in depth by least square fitting, and be computed
To fault throw resolving power and depth relationship template table, finger is provided for the identification and explanation of actual seismic data low order fault
It leads.
The following are made a concrete analysis of for different geological models:
(1) impact analysis of velocity structure
The geological model with identical fault combination feature is separately designed, fills four kinds of different velocity structures respectively,
Middle Fig. 2 a represents shallow-layer (1000-1500m) geological model, Fig. 2 b represents middle-shallow layer (1500-2000m) geological model, Fig. 2 c generation
Table mid-deep strata (2000-2500m) geological model, Fig. 2 d represent deep layer (2800-3300m) geological model, are ground by forward simulation
Study carefully the influence that buried depth (velocity structure) identifies low order fault, and on this basis, it is fixed to carry out subsequent influence factor
Amount analysis.
As buried depth is gradually increased, the earthquake reflected wave dominant frequency and resolution ratio of forward simulation section are gradually decreased, because
And the recognition capability of low order fault is also declined therewith.Fig. 3 a is the Seismic forward mould of shallow-layer (1000-1500m) geological model
Quasi- section, can identify that the tomography of 5m or more, 3m tomography not can recognize substantially substantially；Fig. 3 b is middle-shallow layer (1500-2000m)
The seismic forward simulation section of geological model, can identify the tomography of 7m or more substantially, and the reliability of 5m fault recognizing is obvious
Decline, 3m tomography not can recognize；Fig. 3 c is the seismic forward simulation section of mid-deep strata (2000-2500m) geological model, and Fig. 3 d is
The seismic forward simulation section of deep layer (2800-3300m) geological model can substantially identify that the tomography of 9m or more, 5-7m are disconnected
The reliability of layer identification is decreased obviously, and 3m tomography not can recognize.
(2) impact analysis of dominant frequency of seismic wavelet
For low order fault geological model, the ground of 20Hz, 25Hz, 30Hz, 35Hz, 40Hz, 45Hz, 50Hz is respectively adopted
Shake wavelet dominant frequency has carried out seismic forward simulation, analyzes the influence that dominant frequency of seismic wavelet identifies low order fault, concludes total
The fault recognizing template of different earthquake wavelet dominant frequency is born, as shown in Figure 4.
(3) impact analysis of noise
For the seismic forward simulation section of low order fault geological model, be separately added into 5%, 10%, 15%, 20%,
25%, 30%, 50% noise, analyzes the influence that noise identifies low order fault, and induction and conclusion has gone out containing different proportion
The fault recognizing template of noise, as shown in Figure 5.
On the basis of the impact analysis that dominant frequency of seismic wavelet and noise identify low order fault, induction and conclusion different depth
Lower conventional data and the tomography resolving power template of high-precision data are as shown in fig. 6, draw out fault throw resolution ratio power and depth
Intersection composite curve chart as shown in fig. 7, and tomography resolving power exponential function is obtained by formula fitting, calculated through fitting formula
It is as shown in table 1 to conventional data fault throw resolving power and depth relationship template table, obtain the resolution of high-precision data fault throw
Power and depth relationship template table are as shown in table 2；
1 conventional data fault throw resolving power of table and depth relationship template
2 high-precision data fault throw resolving power of table and depth relationship template
By above-mentioned analysis: seismic data is to the resolving power of tomography and buried depth of strata, wavelet dominant frequency, data noise etc.
Factor relation is close.Depth is bigger, wavelet dominant frequency is lower, noise is bigger, and the resolving power of tomography is lower, that is to say, that point of tomography
The signal-to-noise ratio and resolution ratio for distinguishing power and seismic data are positively correlated, so low sequence can be greatly improved by improving the precision of seismic data
The accuracy of identification of grade tomography.
(4) impact analysis of section dip angle
Design have different section inclination angle acline geological model as shown in figure 8, turn-off be followed successively by from top to bottom 5m,
7m, 9m, 11m, 13m, by forward simulation section as shown in figure 9, induction and conclusion goes out the fault recognizing mould of different co-hades
Version as shown in Figure 10, is recognized and conclusion as follows:
1. when section dip angle >=40 °, the fault plane reflection of 8-13m tomography is weaker, and lineups are staggered, tomography can reliably be known
Not, 6m tomography reduces with section dip angle, and fault plane reflection gradually increases and is connected with interface reflection, and identification certainty reduces；
2. when section dip angle < 40 °, fault plane reflection is suitable with stratum two sides interface reflected intensity, and is connected with interface reflection,
Tomography can be identified according to fault plane reflection feature, but breakpoint clarity reduces.
(5) impact analysis of attitude of stratum
Design positive tomography geological model such as Figure 11 a institute that depth of stratum is incremented by the geological model with Different Strata inclination angle
Show, design depth of stratum successively decrease the geological model with Different Strata inclination angle antithetic faults geological model as figure 12 a shows,
Middle section dip angle is fixed as 70 °, be respectively adopted dominant frequency of seismic wavelet be 40Hz to forward direction tomography geological model shown in 11a with
Antithetic faults geological model shown in 12a carries out seismic forward simulation, obtains the forward simulation section of positive tomography geological model
As shown in figure 11b, the forward simulation section of antithetic faults geological model is obtained as shown in Figure 12b, induction and conclusion goes out Different Strata
The fault recognizing template at inclination angle is as shown in figure 13, is recognized as follows and conclusion:
1. when depth of stratum successively decreases from left to right, the tomography in model be positive normal fault as depicted in fig. 13 a: it is local
When inclination layer is 5 ° -40 °, as stratigraphic dip increases, tomography two sides reflection line-ups gradually becomes wrong from twisting, the changing of the relative positions
It is disconnected, it being capable of reliable recognition tomography.When stratigraphic dip is greater than 40 °, tomography two sides tilted interface reflection line-ups bad break is unknown
Aobvious, transition is the changing of the relative positions, to influence the accurate positioning of breakpoint.
2. when depth of stratum is incremented by from left to right, the tomography in model be Antithetic normal fault as illustrated in fig. 13b: it is local
When inclination layer is 5 ° -40 °, as stratigraphic dip increases, tomography two sides reflection line-ups gradually becomes micro- twisting from twisting, breaks
Layer identification difficulty increases；When stratigraphic dip reaches 40 ° -45 °, the reflection wave imaging of tilted interface is affected by tomography,
Energy jump occurs in transverse direction and generates micro- twisting, it can not reliable recognition tomography；When stratigraphic dip is greater than 45 °, tilted interface
Catoptric imaging effect is deteriorated and cannot even be imaged.
(6) the combined influence factor analysis of section dip angle and stratigraphic dip
Respectively the angle for section and interface be 15 °, 20 °, 25 °, 30 °, 35 °, 40 °, 45 °, 50 °, 55 °, 60 °,
Situation at 65 °, 70 °, 75 °, 80 °, 85 °, 90 °, 95 ° devises the Geological Model of section dip angle and stratigraphic dip while variation
Type, by the combined influence of Analysis of Forward Modeling section dip angle, stratigraphic dip and its angle, summary and induction go out section dip angle with
The fault recognizing module of stratigraphic dip is as shown in figure 14, is recognized as follows and conclusion:
1. stratigraphic dip is less than 30 °: when section dip angle is between 20-40 °, the reflection line-ups changing of the relative positions of tomography two sides,
The ability of fault recognizing is most strong；When section dip angle is greater than 40 °, tomography two sides reflection line-ups is twisting, micro- twisting, tomography
Recognition capability reduces；
2. stratigraphic dip is greater than 40 °, interface catoptric imaging is poor or even cannot be imaged, thus can not reliable recognition it is disconnected
Layer；
3. section dip angle is less than 10 °, fault plane reflection is stronger, and is connected with interface reflection, the reliability of fault recognizing compared with
Difference.
The major influence factors table of 3 fault recognizing of table
The major influence factors table (table 3) and weight proportion (such as Figure 15) that fault recognizing is summarized by analysis and summary, from
As can be seen that the principal element for influencing fault recognizing is mainly the dominant frequency of seismic wavelet, due to buried depth, signal-to-noise ratio in Figure 15
It is all related with dominant frequency, be the principal element of seismic resolution, so the weighing factor of dominant frequency is relatively high, followed by buried depth,
Attitude of stratum, signal-to-noise ratio.Under normal conditions, section dip angle is between 30-80 °, when stratigraphic dip is less than 40 °, attitude of stratum pair
The influence of fault recognizing is higher than the angle of section dip angle and stratum and section.
The limitation that technical solution of the present invention is not limited to the above specific embodiments, it is all to do according to the technique and scheme of the present invention
Technology deformation out, falls within the scope of protection of the present invention.
Claims (4)
1. a kind of quantitative analysis method for influencing low order fault accuracy of identification, which comprises the following steps:
Step 1, on the basis of analysing in depth low order fault geology characteristic and seismic response features, know for low order fault
Other influence factor designs low order fault geological model；
Step 2, by seismic forward simulation, main feature of the low order fault in seismic data is studied；
Step 3, carry out the impact analysis to low order fault accuracy of identification, the fault recognizing under induction and conclusion different affecting factors
Template, fault throw resolution ratio power intersect resultant curve and its template table with depth.
2. the quantitative analysis method according to claim 1 for influencing low order fault accuracy of identification, it is characterised in that: described
In step 1 during carrying out the analysis of Influential Factors of low order fault accuracy of identification, it is directed to buried depth, speed knot respectively
Structure, dominant frequency of seismic wavelet, signal-to-noise ratio, section dip angle, attitude of stratum, stratum and section angle influence low order fault identification essence
The factor of degree designs different types of low order fault geological model.
3. the quantitative analysis method according to claim 1 for influencing low order fault accuracy of identification, it is characterised in that: described
The low order fault geological model designed in step 2 for step 1, by simulating field layout, determining excitation point and connecing
The position of sink simulates epicenter excitation, obtains common-source point earthquake record, then carries out to the common-source point earthquake record that simulation obtains
Pre-stack depth migration imaging finally obtains the seismic response of given geological model as a result, the seismic response of analysis FAULT MODEL is special
Sign, provides foundation for the identification and explanation of tomography.
4. the quantitative analysis method according to claim 1 for influencing low order fault accuracy of identification, it is characterised in that: described
It is that low order fault is had studied by the seismic forward simulation to the low order fault geological model designed in step 1 in step 3
Main feature in seismic data has respectively obtained the fault recognizing template of different earthquake wavelet dominant frequency, has contained through induction and conclusion
The fault recognizing template of different proportion noise, the fault recognizing template at different section inclination angle, Different Strata inclination angle fault recognizing
Conventional data and the tomography of high-precision data point under the fault recognizing template of template, section dip angle and stratigraphic dip, different depth
Distinguish that power identification template, common seismic data intersect resultant curve pair with high precision seismic data fault throw resolution ratio power with depth
Than figure, fault resolution power is obtained with the functional relation of change in depth by least square fitting, and it is disconnected to calculate tomography
Away from resolving power and depth relationship template table, guidance is provided for the identification and explanation of actual seismic data low order fault.
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| CN114063157A (en) * | 2020-07-30 | 2022-02-18 | 中国石油化工股份有限公司 | Method, system, storage medium and electronic device for thin interbed seismic feature analysis |
| CN114624776A (en) * | 2020-12-14 | 2022-06-14 | 中国石油化工股份有限公司 | Quantitative analysis method for fault cementing zone influence fault seismic response characteristic change |
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| CN112394405B (en) * | 2019-08-13 | 2024-08-20 | 中国石油化工股份有限公司 | Concealed fault identification method |
| CN113534237A (en) * | 2020-04-18 | 2021-10-22 | 中国石油化工股份有限公司 | Forward model-based method for quantitatively analyzing resolution of low-order fault of buried hill |
| CN113589368A (en) * | 2020-04-30 | 2021-11-02 | 中国石油化工股份有限公司 | Quantitative analysis method for influence of igneous rock on seismic reflection characteristic change and rule |
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| CN114624776A (en) * | 2020-12-14 | 2022-06-14 | 中国石油化工股份有限公司 | Quantitative analysis method for fault cementing zone influence fault seismic response characteristic change |
| CN114624776B (en) * | 2020-12-14 | 2024-03-19 | 中国石油化工股份有限公司 | Quantitative analysis method for influence of fault cementation zone on fault earthquake response characteristic change |
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