CN107238861B - Normal-moveout spectrum automatic interpretation method and system - Google Patents
Normal-moveout spectrum automatic interpretation method and system Download PDFInfo
- Publication number
- CN107238861B CN107238861B CN201610183148.2A CN201610183148A CN107238861B CN 107238861 B CN107238861 B CN 107238861B CN 201610183148 A CN201610183148 A CN 201610183148A CN 107238861 B CN107238861 B CN 107238861B
- Authority
- CN
- China
- Prior art keywords
- velocity
- root mean
- normal
- initial
- interval velocity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001228 spectrum Methods 0.000 title claims abstract description 86
- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000000977 initiatory effect Effects 0.000 claims 4
- 238000006243 chemical reaction Methods 0.000 claims 2
- 238000004458 analytical method Methods 0.000 description 5
- 230000008901 benefit Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000005457 optimization Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000002939 conjugate gradient method Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000005284 excitation Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 210000004218 nerve net Anatomy 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- 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
- G01V1/303—Analysis for determining velocity profiles or travel times
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
Disclose a kind of normal-moveout spectrum automatic interpretation method and system.This method may include: to obtain the normal-moveout spectrum of the common midpoint gather data based on common midpoint gather data；Based on the normal-moveout spectrum of the common midpoint gather data, acquisition speed pattern function；Based on the rate pattern function, initial root mean square speed and initial interval velocity are obtained；And it is based on initial root mean square speed and initial interval velocity, obtain final interval velocity and final root mean sequare velocity.
Description
Technical field
The present invention relates to field of seismic exploration, more particularly, to a kind of normal-moveout spectrum automatic interpretation method and system.
Background technique
In field of seismic exploration, seimic wave velocity is one of most important parameter in seismic prospecting, it is through at earthquake
Reason and the whole process explained.But in different phase, source, meaning and the application of the parameter are all different.In earthquake
Data handles initial stage, generally all without suitable rate pattern, it is necessary to stack velocity is obtained by conventional velocity analysis, and
And be all stack velocity to be equal to root mean sequare velocity, and be superimposed to carry out dynamic school with this, it obtains stacked section or is folded
Preceding time migration, or time and depth transfer is carried out based on root mean sequare velocity model and is gone forward side by side a stepping line displacement velocity analysis.Therefore, exist
In the processing of oil-gas exploration seismic data, stack velocity analysis is both basic to be also very important in seismic data process
Hold, it is to realize the foundation of seismic prospecting multi-fold CMP trace gather (common midpoint gather) superposition, and support high precision seismic
The basis of image taking speed modeling.
Stack velocity analysis is the way of realization based on normal-moveout spectrum, according to existing between the excitation and reception of seismic signal
NMO (normal moveout) principle is scanned using a series of previously given rate curves, is successively calculating the road CMP trace gather Zhong Ge just
The normal time difference then carries out dynamic school and superposition, m- speed-stack power matrix when obtaining.The explanation of stack velocity spectrum is based on same
Superimposed energy maximum principle exactly can correctly calculate the NMO (normal moveout) and NMO (normal moveout) in each road when scanning speed is correct
The same phase superposition of each track data in CMP trace gather is realized in correction, and stack power at this time is maximum, therefore, the explanation of stack velocity spectrum
It is that relatively reliable on the normal-moveout spectrum and biggish energy group of stack power is analyzed and sorted along time shaft.
In fact, there are many factor that stack velocity spectrum calculating and Explanation Accuracy are influenced in actual seism processing,
Such as random noise in earthquake record, signal-to-noise ratio, complicated structure, the interference of wave, stratigraphic dip etc., these influence factors are not
It may comprehensively be described by mathematical model and be eliminated comprehensively by data processing.Therefore, away from song when actual back wave
Line has not been the hyperbola form in ideal meaning, and stack velocity spectrum would generally show energy group out-focus, on a timeline
The variation tendency of speed is not unique, velocity variations are big or speed is reversed etc..
The condition of seismic prospecting and the signal-to-noise ratio of observational data are limited by due to the precision of stack velocity analysis, in normal-moveout spectrum
On show multi-solution and ambiguity, therefore, the explanation of normal-moveout spectrum substantially uses interactive mode, this is also current routine
The maximum link of manual operation load in seism processing.Therefore, speed automatic interpretation method is also constantly released, these sides
Method is typically all to be based on global optimization approach.Such as based on monte carlo method etc..Such methods have algorithm easily designed, right
Objective function is of less demanding thus the advantages of being widely used.But low efficiency, it cannot be guaranteed that the optimal solution of optimization problem is generated, and
Conclusion is often with randomness.Other is that the method based on local optimal searching includes: Newton method, conjugate gradient method, nerve net
Network method etc..Although such methods have higher computational efficiency, but algorithm is complicated.It generally requires using derivative to be searching extreme point
Effective information is provided.Direct method does not require the analytical property of function, and according to certain mathematical principle, use is few as far as possible
Calculation amount, the position of extreme point is determined by the size of direct comparison function value.
Inventors have found that the result that the normal-moveout spectrum automatic interpretation of the prior art obtains is inaccurate, lead to unreasonable layer
Speed.Therefore, it is necessary to develop a kind of accurate normal-moveout spectrum automatic interpretation method and system.
The information for being disclosed in background of invention part is merely intended to deepen the reason to general background technique of the invention
Solution, and it is known to those skilled in the art existing to be not construed as recognizing or imply that the information is constituted in any form
Technology.
Summary of the invention
The invention proposes a kind of normal-moveout spectrum automatic interpretation method and system, by building model and can be disturbed
And optimizing, the final interval velocity and final root mean sequare velocity of each common point are obtained, realizes accurate normal-moveout spectrum automatic interpretation.
According to an aspect of the invention, it is proposed that a kind of normal-moveout spectrum automatic interpretation method.The method may include: it is based on
Common midpoint gather data obtain the normal-moveout spectrum of the common midpoint gather data；Based on the common midpoint gather data
Normal-moveout spectrum, acquisition speed pattern function；Based on the rate pattern function, initial root mean square speed and initial interval velocity are obtained；
And it is based on initial root mean square speed and initial interval velocity, obtain final interval velocity and final root mean sequare velocity.
According to another aspect of the invention, it is proposed that a kind of normal-moveout spectrum automatic Interpretation System, the system may include: use
In being based on common midpoint gather data, the unit of the normal-moveout spectrum of the common midpoint gather data is obtained；For based on described total
The normal-moveout spectrum of central point trace gather data, the unit of acquisition speed pattern function；For being based on the rate pattern function, obtain just
The unit of beginning root mean sequare velocity and initial interval velocity；And it for being based on initial root mean square speed and initial interval velocity, obtains most
The unit of whole interval velocity and final root mean sequare velocity.
Methods and apparatus of the present invention has other characteristics and advantages, these characteristics and advantages are attached from what is be incorporated herein
It will be apparent in figure and subsequent specific embodiment, or will be in the attached drawing and subsequent specific implementation being incorporated herein
It is stated in detail in example, these the drawings and specific embodiments are used together to explain specific principle of the invention.
Detailed description of the invention
Exemplary embodiment of the present is described in more detail in conjunction with the accompanying drawings, of the invention is above-mentioned and other
Purpose, feature and advantage will be apparent, wherein in exemplary embodiments of the present invention, identical reference label is usual
Represent same parts.
Fig. 1 shows the flow chart of the step of normal-moveout spectrum automatic interpretation method according to the present invention.
Specific embodiment
The present invention will be described in more detail below with reference to accompanying drawings.Although showing the preferred embodiment of the present invention in attached drawing,
However, it is to be appreciated that may be realized in various forms the present invention and should not be limited by the embodiments set forth herein.On the contrary, providing
These embodiments are of the invention more thorough and complete in order to make, and can will fully convey the scope of the invention to ability
The technical staff in domain.
Embodiment 1
Fig. 1 shows the flow chart of the step of normal-moveout spectrum automatic interpretation method.
In this embodiment, normal-moveout spectrum automatic interpretation method according to the present invention may include: step 101, in altogether
Heart point trace gather data, obtain the normal-moveout spectrum of the common midpoint gather data；Step 102, it is based on the common midpoint gather number
According to normal-moveout spectrum, acquisition speed pattern function；Step 103, be based on the rate pattern function, obtain initial root mean square speed and
Initial interval velocity；And step 104, be based on initial root mean square speed and initial interval velocity, obtain final interval velocity and it is final
Root speed.
The embodiment passes through building model and carries out disturbance and optimizing, obtains the final interval velocity and most of each common point
Whole root mean sequare velocity realizes the accurate automatic interpretation of normal-moveout spectrum.
The following detailed description of the specific steps of normal-moveout spectrum automatic interpretation method according to the present invention.
Acquisition speed spectrum
In one example, common midpoint gather data can be based on, the normal-moveout spectrum of common midpoint gather data is obtained.This
Field is it will be appreciated by the skilled person that can obtain common midpoint gather data using various conventional methods known in the art
Normal-moveout spectrum.
In one example, the normal-moveout spectrum of common midpoint gather data can be similar spectrum or coherence spectra.
Specifically, common point (CMP) the trace gather data that can use surface seismic pre stack data generate normal-moveout spectrum.Speed
Spectrum can be similar spectrum, be also possible to coherence spectra.The form of the normal-moveout spectrum of common midpoint gather data is S (t, vrms(t)),
Wherein t is time, vrms(t) be the time be t when stratum root mean sequare velocity, S (t, Vrms(t)) it indicates in (t, vrms(t)) at
Normal-moveout spectrum.
Acquisition speed pattern function
It in one example, can be based on the normal-moveout spectrum of the common midpoint gather data, acquisition speed pattern function.
In one example, acquisition speed pattern function may include: and traverse to sort along time shaft to make to compose energy on normal-moveout spectrum
Maximum root mean sequare velocity is measured, rate pattern function is fitted using the root mean sequare velocity, obtains the multiple of rate pattern function
Coefficient.Wherein, rate pattern function can indicate are as follows:
vrms(t)=v0+α·tβ (1)
In formula (1), t is time, vrms(t) be the time be t when stratum root mean sequare velocity, v0Being is zero the time
When stratum root mean sequare velocity, α, β be undetermined coefficient.
Specifically, the rate pattern function as shown in formula (1) can be introduced.The rate pattern function can be adapted for greatly
Most geological conditions.For certain primary collected seismic data in some specific area, v0, α, β are undetermined coefficient.Cause
This determines that these coefficients need to utilize normal-moveout spectrum.Specific practice is, traversed along time shaft sort make along normal-moveout spectrum spectrum energy S (t,
vrms(t)) maximum root mean sequare velocity vrms(t), then with these root mean sequare velocities vrms(t) fitting formula (1) is gone to, to obtain
Coefficient v0, α, β.It is thus possible to acquisition speed pattern function.Preferably, each common point can so be handled, to obtain
Obtain each corresponding rate pattern function of common point.
Obtain initial root mean square speed and initial interval velocity
In one example, it can be based on the rate pattern function, obtain initial root mean square speed and initial interval velocity.
In one example, it obtains initial root mean square speed and initial interval velocity may include: based on the rate pattern
Function obtains the initial root mean square speed of each common point；And Dix formula is applied, by the initial of each common point
Root mean sequare velocity is converted to the initial interval velocity of each common point.
Specifically, parameter v is being obtained0, after α, β, so that it may when obtaining any under current common point according to formula (1)
The initial root mean square speed v at quarterrms(t), by repeatedly calculating, the initial root mean square speed of available each common point.For
Make root mean sequare velocity significant, interval velocity therefrom is significant in other words, need the initial of each common point
Root mean sequare velocity vrms(t) the initial interval velocity v of each common point is converted to Otto Dix (Dix) formulaint(t).This field
It will be appreciated by the skilled person that various conventional methods known in the art can be used, it is based on initial root mean square speed vrms(t) come
Obtain initial interval velocity vint(t)。
Obtain final interval velocity and final root mean sequare velocity
In one example, it can be based on initial root mean square speed and initial interval velocity, obtain final interval velocity and final
Root mean sequare velocity.
In one example, it obtains final interval velocity and final root mean sequare velocity may include: to each common point
Initial interval velocity is disturbed, the interval velocity after obtaining disturbance；Using Dix formula, the interval velocity after disturbance is converted to and is disturbed
Root mean sequare velocity after dynamic；And in the maximum that normal-moveout spectrum corresponding with the root mean sequare velocity after disturbance is current common point
In the case where normal-moveout spectrum, using the root mean sequare velocity after the interval velocity and disturbance after disturbance as final interval velocity and final root mean square
Speed.
Wherein, the interval velocity after obtaining disturbance may include: to be disturbed at random to the initial interval velocity of each common point
Dynamic, after obtaining disturbance interval velocity；And the interval velocity after disturbance is constrained according to specific geological condition, so that after disturbance
The interval velocity interval velocity that is in each time point bound in.
Specifically, it is based on initial root mean square speed vrms(t) and initial interval velocity vintIt (t), can be to initial interval velocity vint
(t) it optimizes.The optimization can be along time shaft progress, i.e., to the initial interval velocity v at each time pointint(t) it carries out
Disturbance, which can be random perturbation, and disturb result should in the bound of interval velocity at every point of time (that is,
According to specific geological condition to the interval velocity v after disturbanceint(t) it is constrained, so that the interval velocity v after disturbanceint(t) in every
In the bound of the interval velocity at a time point), in this way, the interval velocity after available disturbanceFor it is each concentrically
Point can apply Dix formula, by the interval velocity after disturbanceRoot mean sequare velocity after being converted to disturbance
It is then possible to judge normal-moveout spectrum S (t, vrms(t)) in the root mean sequare velocity after disturbanceCorresponding speed
Spectrum whether be current common point maximum speed spectrum Smax.It is not in normal-moveout spectrum corresponding with the root mean sequare velocity after disturbance
The maximum speed of current common point composes SmaxIn the case where, still retain initial interval velocity vint(t) and initial root mean square speed vrms
(t), it optimizes again, that is, abovementioned steps are repeated, to the initial interval velocity v at each time pointint(t) carry out disturbance and
Constraint, the interval velocity after obtaining disturbanceWith the root mean sequare velocity after disturbance
S is composed in the maximum speed that normal-moveout spectrum corresponding with the root mean sequare velocity after disturbance is current common pointmaxFeelings
Under condition, by the interval velocity after disturbanceWith the root mean sequare velocity after disturbanceFinal interval velocity as current point in time
With final root mean sequare velocity.
In this way, multiple random perturbation and optimizing can be carried out to each time point of each common point, institute is finally obtained
There are the final interval velocity and final root mean sequare velocity of common midpoint gather data at every point of time, realizes to the accurate of normal-moveout spectrum
Automatic interpretation.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The beneficial effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
Embodiment 2
According to an embodiment of the invention, providing a kind of normal-moveout spectrum automatic Interpretation System, the system may include: to be used for
Based on common midpoint gather data, the unit of the normal-moveout spectrum of the common midpoint gather data is obtained；For based in described be total to
The normal-moveout spectrum of heart point trace gather data, the unit of acquisition speed pattern function；For being based on the rate pattern function, obtain initial
The unit of root mean sequare velocity and initial interval velocity；And it for being based on initial root mean square speed and initial interval velocity, obtains final
The unit of interval velocity and final root mean sequare velocity.
The embodiment passes through building model and carries out disturbance and optimizing, obtains the final interval velocity and most of each common point
Whole root mean sequare velocity realizes the accurate automatic interpretation of normal-moveout spectrum.
In one example, acquisition speed pattern function may include: and traverse to sort along time shaft to make to compose energy on normal-moveout spectrum
Maximum root mean sequare velocity is measured, rate pattern function is fitted using the root mean sequare velocity, obtains the multiple of rate pattern function
Coefficient, wherein the rate pattern function representation are as follows:
vrms(t)=v0+α·tβ
Wherein, t is time, vrms(t) be the time be t when stratum root mean sequare velocity, v0Stratum when be the time being zero
Root mean sequare velocity, α, β be undetermined coefficient.
In one example, it obtains initial root mean square speed and initial interval velocity may include: based on the rate pattern
Function obtains the initial root mean square speed of each common point；And Dix formula is applied, by the initial of each common point
Root mean sequare velocity is converted to the initial interval velocity of each common point.
In one example, it obtains final interval velocity and final root mean sequare velocity may include: to each common point
Initial interval velocity is disturbed, the interval velocity after obtaining disturbance；Using Dix formula, the interval velocity after disturbance is converted to and is disturbed
Root mean sequare velocity after dynamic；It and is the maximum of current common point in normal-moveout spectrum corresponding with the root mean sequare velocity after disturbance
In the case where normal-moveout spectrum, using the root mean sequare velocity after the interval velocity and disturbance after disturbance as final interval velocity and final root mean square
Speed.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The beneficial effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
Various embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes are obvious for the those of ordinary skill in art field.The selection of term used herein, purport
In the principle, practical application or improvement to the technology in market for best explaining each embodiment, or make the art
Other those of ordinary skill can understand each embodiment disclosed herein.
Claims (8)
1. a kind of normal-moveout spectrum automatic interpretation method, comprising:
Based on common midpoint gather data, the normal-moveout spectrum of the common midpoint gather data is obtained；
Based on the normal-moveout spectrum of the common midpoint gather data, acquisition speed pattern function；
Based on the rate pattern function, initial root mean square speed and initial interval velocity are obtained；And
Based on initial root mean square speed and initial interval velocity, final interval velocity and final root mean sequare velocity are obtained；
Wherein, it obtains final interval velocity and final root mean sequare velocity includes:
The initial interval velocity of each common point is disturbed, the interval velocity after obtaining disturbance；
Using Dix formula, the interval velocity after disturbance is converted into the root mean sequare velocity after disturbance；And
It, will in the case where normal-moveout spectrum corresponding with the root mean sequare velocity after disturbance is the maximum speed spectrum of current common point
The root mean sequare velocity after interval velocity and disturbance after disturbance is as final interval velocity and final root mean sequare velocity.
2. normal-moveout spectrum automatic interpretation method according to claim 1, wherein acquisition speed pattern function includes: along the time
Axis traversal, which sorts, makes the maximum root mean sequare velocity of spectrum energy on normal-moveout spectrum, is fitted rate pattern letter using the root mean sequare velocity
Number obtains multiple coefficients of rate pattern function,
Wherein, the rate pattern function representation are as follows:
vrms(t)=v0+α·tβ
Wherein, t is time, vrms(t) be the time be t when stratum root mean sequare velocity, v0Stratum when be the time being zero it is equal
Root speed, α, β are undetermined coefficient.
3. normal-moveout spectrum automatic interpretation method according to claim 1, wherein obtain initial root mean square speed and initiation layer speed
Degree includes:
Based on the rate pattern function, the initial root mean square speed of each common point is obtained；And
Using Dix formula, by the initiation layer speed that the initial root mean square rate conversion of each common point is each common point
Degree.
4. normal-moveout spectrum automatic interpretation method according to claim 1, wherein obtaining the interval velocity after disturbing includes:
Random perturbation is carried out to the initial interval velocity of each common point, the interval velocity after obtaining disturbance；And
The interval velocity after disturbance is constrained according to specific geological condition, so that the interval velocity after disturbance is in each time point
Interval velocity bound in.
5. normal-moveout spectrum automatic interpretation method according to claim 1, wherein the normal-moveout spectrum of the common midpoint gather data
It is similar spectrum or coherence spectra.
6. a kind of normal-moveout spectrum automatic Interpretation System, comprising:
For being based on common midpoint gather data, the unit of the normal-moveout spectrum of the common midpoint gather data is obtained；
For the normal-moveout spectrum based on the common midpoint gather data, the unit of acquisition speed pattern function；
For being based on the rate pattern function, the unit of initial root mean square speed and initial interval velocity is obtained；And
For being based on initial root mean square speed and initial interval velocity, the unit of final interval velocity and final root mean sequare velocity is obtained；
Wherein, it obtains final interval velocity and final root mean sequare velocity includes:
The initial interval velocity of each common point is disturbed, the interval velocity after obtaining disturbance；
Using Dix formula, the interval velocity after disturbance is converted into the root mean sequare velocity after disturbance；And
It, will in the case where normal-moveout spectrum corresponding with the root mean sequare velocity after disturbance is the maximum speed spectrum of current common point
The root mean sequare velocity after interval velocity and disturbance after disturbance is as final interval velocity and final root mean sequare velocity.
7. normal-moveout spectrum automatic Interpretation System according to claim 6, wherein acquisition speed pattern function includes: along the time
Axis traversal, which sorts, makes the maximum root mean sequare velocity of spectrum energy on normal-moveout spectrum, is fitted rate pattern letter using the root mean sequare velocity
Number obtains multiple coefficients of rate pattern function,
Wherein, the rate pattern function representation are as follows:
vrms(t)=v0+α·tβ
Wherein, t is time, vrms(t) be the time be t when stratum root mean sequare velocity, v0Stratum when be the time being zero it is equal
Root speed, α, β are undetermined coefficient.
8. normal-moveout spectrum automatic Interpretation System according to claim 6, wherein obtain initial root mean square speed and initiation layer speed
Degree includes:
Based on the rate pattern function, the initial root mean square speed of each common point is obtained；And
Using Dix formula, by the initiation layer speed that the initial root mean square rate conversion of each common point is each common point
Degree.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610183148.2A CN107238861B (en) | 2016-03-28 | 2016-03-28 | Normal-moveout spectrum automatic interpretation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610183148.2A CN107238861B (en) | 2016-03-28 | 2016-03-28 | Normal-moveout spectrum automatic interpretation method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107238861A CN107238861A (en) | 2017-10-10 |
| CN107238861B true CN107238861B (en) | 2019-01-08 |
Family
ID=59983284
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610183148.2A Active CN107238861B (en) | 2016-03-28 | 2016-03-28 | Normal-moveout spectrum automatic interpretation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107238861B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113341461B (en) * | 2021-06-10 | 2023-09-01 | 中国石油大学(北京) | Earthquake velocity prediction method, earthquake velocity prediction device and server |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6253157B1 (en) * | 1998-12-14 | 2001-06-26 | Exxonmobil Upstream Research Co. | Method for efficient manual inversion of seismic velocity information |
| CN1797033A (en) * | 2004-12-29 | 2006-07-05 | 中国石油天然气集团公司 | Method for raising precision of shifted image before superposition by using root mean square velocity |
| CN102043167A (en) * | 2009-10-23 | 2011-05-04 | 中国石油化工股份有限公司 | Curved earth surface seismic data velocity analysis method |
| CN103424772A (en) * | 2012-05-24 | 2013-12-04 | 中国石油化工股份有限公司 | Reservoir shear wave velocity prediction method based on rock physics |
| CN103713315A (en) * | 2012-09-28 | 2014-04-09 | 中国石油化工股份有限公司 | Seismic anisotropy parameter full waveform inversion method and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7493241B2 (en) * | 2003-07-23 | 2009-02-17 | Lee Wook B | 3D velocity modeling, with calibration and trend fitting using geostatistical techniques, particularly advantageous for curved for curved-ray prestack time migration and for such migration followed by prestack depth migration |
-
2016
- 2016-03-28 CN CN201610183148.2A patent/CN107238861B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6253157B1 (en) * | 1998-12-14 | 2001-06-26 | Exxonmobil Upstream Research Co. | Method for efficient manual inversion of seismic velocity information |
| CN1797033A (en) * | 2004-12-29 | 2006-07-05 | 中国石油天然气集团公司 | Method for raising precision of shifted image before superposition by using root mean square velocity |
| CN102043167A (en) * | 2009-10-23 | 2011-05-04 | 中国石油化工股份有限公司 | Curved earth surface seismic data velocity analysis method |
| CN103424772A (en) * | 2012-05-24 | 2013-12-04 | 中国石油化工股份有限公司 | Reservoir shear wave velocity prediction method based on rock physics |
| CN103713315A (en) * | 2012-09-28 | 2014-04-09 | 中国石油化工股份有限公司 | Seismic anisotropy parameter full waveform inversion method and device |
Non-Patent Citations (2)
| Title |
|---|
| "Automatic picking and its application";Lin Zhang;《Stanford Exploration Project》;19971218;第281-299页 |
| "三维叠前深度偏移速度分析及蒙特卡洛自动层速度拾取";陈志德 等;《地球物理学报》;20020331;第45卷(第2期);第246-254页 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107238861A (en) | 2017-10-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106405651B (en) | Full waveform inversion initial velocity model construction method based on logging matching | |
| CN103837893B (en) | Acoustic logging bearing calibration based on VSP data | |
| CN104730579B (en) | A kind of joint static correcting method of ripple in length and breadth based on calculation of near surface shear velocity inverting | |
| CN105182408A (en) | Manufacturing method and device for synthesizing earthquake record | |
| Piana Agostinetti et al. | Assessing uncertainties in high-resolution, multifrequency receiver-function inversion: A comparison with borehole data | |
| CN102901985A (en) | Depth domain layer speed correcting method suitable for undulating surface | |
| WO2013066682A1 (en) | Inversion-based workflow for processing nuclear density images in high-angle and horizontal wells | |
| Abbad et al. | Automatic nonhyperbolic velocity analysis | |
| CN107390266A (en) | Speed update method and pre-stack depth migration velocity modeling method based on angle gathers | |
| CN107238861B (en) | Normal-moveout spectrum automatic interpretation method and system | |
| Jiang et al. | 3D seismic geometry quality control and corrections by applying machine learning | |
| Zhang et al. | Phase arrival picking for bridging multi-source downhole microseismic data using deep transfer learning | |
| CN107643541B (en) | Normal-moveout spectrum means of interpretation based on rate pattern | |
| CN105445793B (en) | A kind of method and device for determining bad track data | |
| CN105445788B (en) | A kind of automatic means of interpretation of normal-moveout spectrum based on model and global optimizing | |
| Cichostępski et al. | Simultaneous inversion of shallow seismic data for imaging of sulfurized carbonates | |
| CN107229069B (en) | The method that a kind of pair of common receiver data trace gather carries out velocity analysis | |
| WO2023123971A1 (en) | Vsp-based level calibration method and apparatus for depth-domain seismic profile | |
| CN108897039B (en) | The more wave matching process of DTW based on the control of layer position | |
| Wang et al. | Joint rough sets and Karhunen-Loève transform approach to seismic attribute selection for porosity prediction in a Chinese sandstone reservoir | |
| CN106226815A (en) | The acquisition methods of converted wave velocity equivalent comparison and converted-wave velocity analysis method | |
| Biryol et al. | Imaging the shallow crust with local and regional earthquake tomography | |
| CA2533011C (en) | Method for bispectral picking of anelliptical nmo correction parameters | |
| CN109857979A (en) | A kind of log approximating method based on wavelet analysis and BP neural network | |
| CN107179548B (en) | A kind of pre-stack seismic imaging method based on true earth's surface |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |