CN103913768A - Method and device for modeling superficial layer in earth surface based on seismic wave data - Google Patents
Method and device for modeling superficial layer in earth surface based on seismic wave data Download PDFInfo
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Abstract
The invention discloses a method and device for modeling a superficial layer in an earth surface based on seismic wave data. The method includes the steps that seismic wave original data are preprocessed, a first model is obtained, the travel time and the offset distance of early-reached waves are determined based on the first model and the interesting depth; observation data about the early-reached waves are extracted from the original data according to the travel time and the offset distance; calculating data about the early-reached waves are generated according to the determined travel time ts and the determined offset distance on the basis of the first model; data field fitting is performed on the observation data and the calculating data so that the gradient can be obtained, and therefore a speed updating model is further obtained; the first model and the speed updating model are overlapped to obtain a second model, and the steps are executed repeatedly until the obtained speed updating model reaches the global optimum. Only part of early-reached wave information is used, nonlinearity of a target function is reduced, small offset distance information is adopted, error accumulation is reduced, and therefore by means of the method and device for modeling the superficial layer in the earth surface based on the seismic wave data, the global optimal solution can be converged more easily.
Description
Technical field
The present invention relates to seismic exploration technique, specifically, relate to a kind of method and device that based on Seismic Data, earth's surface middle-shallow layer is carried out modeling in seismic prospecting.
Background technology
Seismic prospecting is the difference of utilizing underground medium elasticity and density, the response by observation and analysis the earth to artificial excitation's seismic event, the geophysical exploration method of the character and form of deduction subterranean strata.Seismic prospecting is the important means that before probing, exploration oil, natural gas source, solid Resource geology are looked for ore deposit, is used widely at aspects such as coalfield and engineering geologic investigation, Study on Regional Geology and earth's crust researchs.
With manual method earthquake-wave-exciting, when to underground propagation, meet the different rock stratum interphase of medium character on earth's surface.To there is reflection and refraction in seismic event, in earth's surface or well, receive this seismic event with wave detector.Character and the structure of the position of the seismic signal of receiving and earthquake source characteristic, geophone station, the subterranean strata of seismic event process are relevant.By seismic record being processed and being explained, can infer the character and form of subterranean strata.Seismic prospecting, in the level of detail of layering and the precision of reconnoitring, is all better than other geophysical exploration methods.
But in seismic prospecting, the technology of shallow surface being carried out to modeling is the difficult point of velocity modeling always.At present, comparatively conventional is the method for first arrival based on ray class tomographic inversion while walking.These class methods are calculated simple, do not require background velocity field accurately, are applicable to complicated earth surface situation, are the common methods that solves in recent years near surface and shallow-layer velocity modeling.But, the shortest path principle of this method based on high frequency hypothesis, in the situation that Low Velocity Body is grown, there is " blind area " of modeling in this technology.In addition, ray class methods are to radiographic density sensitivity.When velocity variations is violent, even high-velocity anomaly body, due to the generation of total reflection phenomenon, will have a strong impact on the density of ray, then reduce the precision of inverting.
In addition, in actual data application, primary wave data to pick up workload huge, manually pick up and have error, and when being difficult to pick up exactly all primary wave data under the complicated situation of earth's surface.
Although, in prior art, also exist by Full wave shape inverting (Full Waveform Inversion, FWI) method and carry out the technology of modeling.But the realization of this new method also has a lot of restrictions, as thering is for data the feature of large offseting distance, low-frequency information etc., could use.
Therefore, need to provide a kind of and so strictly and again can accurately not reflect the modeling method and technique of list structure practically to source book requirement.
Summary of the invention
The present invention is directed to the deficiencies in the prior art, proposed a kind of method of based on Seismic Data, shallow surface being carried out modeling, it comprises the following steps:
S101, seismic event source book is carried out to pre-service, and obtain the first model, determine early to wave propagation time t based on this first model and the degree of depth interested
sand offset distance;
S102, according to described travel-time t
scome from source book, to extract about the observation data d of morning to ripple with offset distance
obs;
S103, adopt wave equation method on described the first model basis according to definite travel-time t
sproduce about the computational data d of morning to ripple with offset distance
cal;
S104, based on inversion algorithm to described observation data d
obswith described computational data d
calcarry out data field matching, to obtain gradient, thereby further obtain speed Renewal model;
S105, described the first model and speed Renewal model are superposeed and obtain the second model, also repeatedly perform step S103 and step S104 using described the second model as the first model, until the speed Renewal model of asking for while reaching a preset value, is exported the second model finally obtaining specifically as the final speed model of the true stratal configuration of reflection.
In the present invention, to ripple be early all ripples of propagating at ground floor basement rock of arrival wave detector.
According to one embodiment of present invention, in step S101, travel-time t
sbe chosen for and be less than the time that zero big gun arrives apart from reflection wave.
According to one embodiment of present invention, in step S101, determine offset distance in conjunction with near surface actual conditions.
According to one embodiment of present invention, in step S104, the objective function of described inversion algorithm is error function C(m):
Described preset value is for working as observation data d
obswith computational data d
calthe error function of least square approach the speed Renewal model of 1 o'clock.
According to one embodiment of present invention, in step S104, described gradient is by adopting Adjoint State Method to obtain.
In one embodiment, described gradient is calculated by following formula:
Wherein, B is for just calculating son,
represent to align the sub model parameter differentiate of calculation,
for main story wave field, B
-ltfor residual error anti-pass operator, Δ d is observation data d
obswith computational data d
calbetween error.
In order to make model converge to more quickly and accurately global optimum, in step S101, can adopt first arrival chromatography conversion method to obtain described the first model.
According to another aspect of the present invention, also provide a kind of device that based on Seismic Data, shallow surface is carried out modeling, it comprises:
Pretreatment unit, it carries out pre-service to seismic event source book, and obtains the first model, determines early to wave propagation time t based on this first model and the degree of depth interested
sand offset distance;
Early, to ripple observation data extraction element, it is according to described travel-time t
scome from source book, to extract about the observation data d of morning to ripple with offset distance
obs;
Early to ripple computational data extraction element, its adopt wave equation method on described the first model basis for definite travel-time t
sproduce about the computational data d of morning to ripple with offset distance
cal;
Matching device, its based on inversion algorithm to described observation data d
obscarry out data field matching with described computational data dcal, thus the gradient of asking for, and then ask for speed Renewal model;
Final speed model iteration output unit, it superposes described the first model and speed Renewal model to obtain the second model, send described morning to using described the second model as the first model to ripple computational data extraction element, and repeatedly carry out morning to ripple computational data and extract and matching, until the speed Renewal model of asking in described matching device while reaching a preset value, is exported the second model finally obtaining specifically as the final speed model of the true stratal configuration of reflection.
The present invention has brought following beneficial effect:
Early, to waveform inverting, compared with Full wave shape inverting, only use part early to ripple information, reduce the non-linear of objective function, adopted little offset distance information, reduced the accumulation of error, therefore morning to waveform inverting more easily converges to globally optimal solution, the risk that the minimizing cycle jumps.This method is only applicable to solving the modeling problem of near surface and middle-shallow layer, to early having limitation to wave action scope region in addition.
Other features and advantages of the present invention will be set forth in the following description, and partly from instructions, become apparent, or understand by implementing the present invention.Object of the present invention and other advantages can be realized and be obtained by specifically noted structure in instructions, claims and accompanying drawing.
Accompanying drawing explanation
Fig. 1 has shown according to one embodiment of present invention to the schematic diagram of morning to the definition of ripple;
Fig. 2 has shown the process flow diagram that adopts the inventive method to carry out shallow surface modeling;
Fig. 3 has shown the schematic diagram of the true velocity model of shallow surface;
Fig. 4 has shown initial velocity model schematic diagram given while adopting the inventive method to carry out inverting;
Fig. 5 has shown the schematic diagram of tomographic inversion result when first arrival is walked;
Fig. 6 has shown and adopts method of the present invention to carry out the rate pattern schematic diagram that modeling obtains.
Embodiment
Describe embodiments of the present invention in detail below with reference to accompanying drawing, to the present invention, how application technology means solve technical matters whereby, and the implementation procedure of reaching technique effect can fully understand and implement according to this.It should be noted that, only otherwise form conflict, each feature in various embodiments of the present invention and each embodiment can mutually combine, and the technical scheme forming is all within protection scope of the present invention.
Seismic prospecting process is made up of earthquake data acquisition, data processing and seismic data interpretation three phases.The present invention processes and is beneficial to final data interpretation mainly for the source book gathering.
First simply introduce the morning of the present invention's proposition to the key concept of ripple below.
Early the same with primary wave to ripple, do not refer in particular in the physical sense the ripple of a certain type.In fact it comprised the information of a lot of ripples, as direct wave, first broadcast, transmitted wave, diving Wave, refraction wave etc.Morning to the English full name of ripple is early arrival waves.Therefore and primary wave (first arrival wave) have very large difference.
Primary wave refers to the one in ripples such as being detected the direct wave arriving at first that first device record, first broadcast, transmitted wave.Early refer to that to ripple first arrival is detected the set of these ripples that device records after arriving in a period of time, as shown in Figure 1, what in the region between the line being represented by mark 10 and 11, comprise is early to ripple information.
At nearly offset distance, to ripple main manifestations be early the set of the ripple of propagating more than ground floor reflecting interface.These ripples, not through reflecting interface transformation, contain the abundant information of Velocity anomalies in this region in its shape information.Therefore, the present invention utilizes these characteristic waves, by the means of waveform inversion, completes the reconstruction to these Velocity anomalies.
And mainly containing the refraction wave information from deep layer at large offseting distance, these information, in Full wave shape refutation process, have great significance to the estimation of deep model.Therefore,, near surface, middle layer velocity modeling, we will avoid these refraction information.
Morning to ripple integrates and records main manifestations as linear feature at big gun.Go the linear disturbance such as ground roll during in conventional processing, often damaged the early information to ripple, and conventional modeling, imaging means do not need early, to ripple information, therefore in a lot of situations, to be early taken as noise jamming to ripple and to remove substantially.Early to waveform inverting modeling, during to the walking of ripple and shape information, therefore need the processing to early protected width, fidelity to ripple the morning that mainly uses nearly offset distance in actual data application process.
Early, to the utilization of waveform inverting modeling method early to this characteristic wave shape information of ripple, realize the velocity modeling near surface, middle-shallow layer based on Full wave shape inversion theory.The same with Full wave shape inverting, based on wave equation theory, the kinematics and the dynamic information that use ripple to propagate.Different, the present invention only uses the early information to ripple, and and unlike Full wave shape inverting, simulate the information of all-wave field, complete the data fitting of all-wave field.Therefore, reduced the complexity of problem, made convergence process more easily reach globally optimal solution.In addition, according to for problem, the reconstruction of the Velocity anomalies of near surface and middle-shallow layer, therefore we adopt the information of little offset distance, reduce initial model inaccurate cumulative errors of bringing, the risk that the reduction cycle jumps, accelerating convergence process.
Fig. 1 has shown primary wave and the early contrast to ripple.Wherein, primary wave is those ripples that line 11 is indicated, and morning to ripple is the following 200ms of line 11 left and right line 10 above parts.Therefore, can find out, morning to the ripple of the present invention's definition is the set of the ripple in a period of time after primary wave arrives, and it contains abundanter formation information than primary wave.
In near surface and middle-shallow layer modeling process, morning to ripple has been brought into play vital role.Information while utilizing first break picking to involve after first arrival one section in window, can bring the interfere informations such as low layer refraction wave and cause the mistake convergence of inverting.Therefore, just drilling that to simulate accurately morning to the ripple mating with real data be the basis to the waveform inversion of ripple early.
In complicated near-surface velocity anomaly and complex dielectrics situation, waveform inversion method can make up " blind area " of traditional ray theory modeling.Therefore, we not only need accurately simulation early to the kinematics information of ripple, early also very important to the dynamic information of ripple.Based on this, for the velocity modeling of near surface and middle-shallow layer, need to avoid the information receiving at large offseting distance wave detector from the refraction wave that contains deeper formation information of deep layer etc., so morning to the ripple before the ground floor reflecting interface reflection wave of nearly offset distance arrives is the emphasis that we simulate.
In order accurately to simulate its kinematics and dynamic characteristic, the present invention is to early adopting the method for wave equation to the simulation of ripple, and wherein Acoustic Wave-equation is similar to the form that can write an accepted way of doing sth (1).And the selection perceived model of offset distance and near surface situation and determine, generally in 2km～3km left and right.Simulated time is less than zero-offset reflection wave time of arrival, and this time can pick up from real data.
In formula: P is pressure field, and Vx, Vz are respectively horizontal and vertical velocity field, k=ρ v2, ts is early to wave propagation time, generally chooses to zero-offset reflection wave time of arrival (or more obvious reflective layer reflects ripple time of arrival).
Next, the problem of waveform inversion is discussed.Geophysical inversion is divided into the inverting of ray class, linear inversion and non-linear inversion three major types.There is " blind area " of modeling in the inverting of ray class, the block of especially growing at middle-shallow layer low velocity layer, and these class methods are difficult to provide rate pattern more accurately.And linear inversion needs tentation data local linear, conventionally local inverting is had to good effect, and require a background velocity field more accurately.
Therefore, nonlinear inversion method will be the Perfected process of processing middle-shallow layer modeling.The Full wave shape inversion theory based on least square that Tarantola proposes has played very large prograding to waveform inversion.Morning to ripple is introduced this theoretical system by the present invention, utilizes morning to ripple information, completes the early waveform inversion to ripple.
First, definition error functional is:
Wherein: C is error function, L2 is error functional, and Δ d is observation data and simulated data residual error.The process of computational data and observation data matching, the namely process of the true model of Model approximation.The magnanimity that gradient is asked in order to avoid Frechet matrix is calculated, and can adopt Adjoint State Method, can be written as following formula:
Wherein: m is model parameter, U is main story wave field, and B is for just calculating son, and Δ d is the error between observation data and computational data, B
-ltfor residual error anti-pass operator.Making gradient function is 0, tries to achieve Disturbance Model.
Finally, true model is initial model and Disturbance Model sum, as 4 formulas:
M＝M
0+ΔM （4）
Wherein: M is true model, M
0for initial model, Δ M is Disturbance Model.
Morning to waveform inverting is a nonlinear process.Therefore, this process often needs repeatedly iteration.In addition,, because gradient only can represent the convergence direction of error, need to ask for a suitable step-length toward contact.Suitable step-length is chosen counting yield and the precision that can accelerate inverting.This step-length can be calculated by efficient solution such as such as method of conjugate gradient, L-BFGS etc.But, the technology that also has a lot of other methods about primary wave waveform inversion and step-length to choose in prior art.For not fuzzy the present invention, do not discuss in detail various such technology here.
Introduce the whole implementation procedure of the inventive method below, in conjunction with Fig. 2 according to computer implemented mode.
The method of as shown in Figure 2, based on Seismic Data, shallow surface being carried out to modeling starts from step S101.In this step, the seismic event source book gathering is carried out to pre-service, and obtain the first model M
0, based on this first model M
0determine early to wave propagation time t with the degree of depth interested
sand offset distance.Wherein, determine offset distance in conjunction with near surface actual conditions.In one embodiment of the invention, for making model converge to more accurately and rapidly global optimum, can adopt first arrival chromatography conversion method to obtain initial model M0, i.e. the first model.
In step S102, according to travel-time t
scome from source book, to extract about the observation data d of morning to ripple with offset distance
obs.
In step S103, adopt wave equation method in the first model M
0on basis according to definite travel-time t
sproduce about the computational data d of morning to ripple with offset distance
cal.
In step S104, based on inversion algorithm to observation data d
obswith computational data d
calcarry out data field matching, to obtain gradient, thereby further obtain speed Renewal model Δ M.
In step S105, by the first model M
0superpose and obtain the second model M with speed Renewal model Δ M, using the second model as the first model M
0and repeatedly perform step S103 and step S104, until the speed Renewal model of asking for while reaching a preset value, is exported the second model M finally obtaining specifically as the final speed model of the true stratal configuration of reflection.
In step S104, the objective function of inversion algorithm is error function C(m):
It also can represent like that according to formula (2).
Preset value is for working as observation data d
obswith computational data d
calthe error function of least square approach the speed Renewal model of 1 o'clock.
In step S104, gradient is by adopting Adjoint State Method to obtain, as mentioned above.
According to another aspect of the present invention, also provide a kind of device that based on Seismic Data, shallow surface is carried out modeling, it comprises:
Pretreatment unit, it carries out pre-service to seismic event source book, and obtains the first model, determines early to wave propagation time t based on this first model and the degree of depth interested
sand offset distance;
Early, to ripple observation data extraction element, it is according to described travel-time t
scome from source book, to extract about the observation data d of morning to ripple with offset distance
obs;
Early to ripple computational data extraction element, its adopt wave equation method on described the first model basis for definite travel-time t
sproduce about the computational data d of morning to ripple with offset distance
cal;
Matching device, its based on inversion algorithm to described observation data d
obscarry out data field matching with described computational data dcal, thus the gradient of asking for, and then ask for speed Renewal model;
Final speed model iteration output unit, it superposes described the first model and speed Renewal model to obtain the second model, send described morning to using described the second model as the first model to ripple computational data extraction element, and repeatedly carry out morning to ripple computational data and extract and matching, until the speed Renewal model of asking in described matching device is while reaching a preset value, the second model finally obtaining is specifically exported as the final speed model of the true stratal configuration of reflection
Wherein, to ripple information be early the information of all ripples of propagating at ground floor basement rock of arrival wave detector.
Fig. 3 has shown the true velocity model of shallow surface.As shown in the figure, dark circle represents high-velocity anomaly body, and white circle represents low-velocity zone.
Fig. 4 has shown initial velocity model given while adopting the inventive method to carry out inverting.And Fig. 5 has shown tomographic inversion result when first arrival is walked.Find out thus, it does not reflect true velocity model exactly.In Fig. 6, can find out that adopting method of the present invention to carry out the rate pattern that modeling obtains has reflected actual conditions more exactly.In order to make method of the present invention converge to more quickly global optimum, its initial velocity model adopting can be the first arrival model that chromatography obtains while walking.
Although the disclosed embodiment of the present invention as above, the embodiment that described content just adopts for the ease of understanding the present invention, not in order to limit the present invention.Technician in any the technical field of the invention; do not departing under the prerequisite of the disclosed spirit and scope of the present invention; can do any modification and variation what implement in form and in details; but scope of patent protection of the present invention, still must be as the criterion with the scope that appending claims was defined.
Claims (9)
1. a method of based on Seismic Data, shallow surface being carried out modeling, is characterized in that, comprises the following steps:
S101, seismic event source book is carried out to pre-service, and obtain the first model, determine early to wave propagation time t based on this first model and the degree of depth interested
sand offset distance;
S102, according to described travel-time t
scome from source book, to extract about the observation data d of morning to ripple with offset distance
obs;
S103, adopt wave equation method on described the first model basis according to definite travel-time t
sproduce about the computational data d of morning to ripple with offset distance
cal;
S104, based on inversion algorithm to described observation data d
obswith described computational data d
calcarry out data field matching, to obtain gradient, thereby further obtain speed Renewal model;
S105, described the first model and speed Renewal model are superposeed and obtain the second model, also repeatedly perform step S103 and step S104 using described the second model as the first model, until the speed Renewal model of asking for while reaching a preset value, is exported the second model finally obtaining specifically as the final speed model of the true stratal configuration of reflection.
2. the method for claim 1, is characterized in that, is early all ripples of propagating at ground floor basement rock of arrival wave detector to ripple.
3. the method for claim 1, is characterized in that, in step S101, and travel-time t
sbe chosen for and be less than the time that zero big gun arrives apart from reflection wave.
4. the method for claim 1, is characterized in that, in step S101, determines offset distance in conjunction with near surface actual conditions.
5. the method for claim 1, is characterized in that, in step S104, the objective function of described inversion algorithm is error function C(m):
Described preset value is for working as observation data d
obswith computational data d
calthe error function of least square approach the speed Renewal model of 1 o'clock.
6. method as claimed in claim 5, is characterized in that, in step S104, described gradient is by adopting Adjoint State Method to obtain.
7. method as claimed in claim 6, is characterized in that, described gradient is calculated by following formula:
Wherein, B is for just calculating son,
represent to align the sub model parameter differentiate of calculation,
for main story wave field, B
-ltfor residual error anti-pass operator, Δ d is observation data d
obswith computational data d
calbetween error.
8. the method for claim 1, is characterized in that, in step S101, adopts first arrival chromatography conversion method to obtain described the first model.
9. a device that based on Seismic Data, shallow surface is carried out modeling, is characterized in that, comprising:
Pretreatment unit, it carries out pre-service to seismic event source book, and obtains the first model, determines early to wave propagation time t based on this first model and the degree of depth interested
sand offset distance;
Early, to ripple observation data extraction element, it is according to described travel-time t
scome from source book, to extract about the observation data d of morning to ripple with offset distance
obs;
Early to ripple computational data extraction element, its adopt wave equation method on described the first model basis for definite travel-time t
sproduce about the computational data d of morning to ripple with offset distance
cal;
Matching device, its based on inversion algorithm to described observation data d
obscarry out data field matching with described computational data dcal, thus the gradient of asking for, and then ask for speed Renewal model;
Final speed model iteration output unit, it superposes described the first model and speed Renewal model to obtain the second model, send described morning to using described the second model as the first model to ripple computational data extraction element, and repeatedly carry out morning to ripple computational data and extract and matching, until the speed Renewal model of asking in described matching device is while reaching a preset value, the second model finally obtaining is specifically exported as the final speed model of the true stratal configuration of reflection
Wherein, to ripple information be early the information of all ripples of propagating at ground floor basement rock of arrival wave detector.
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| CN109655890A (en) * | 2017-10-11 | 2019-04-19 | 中国石油化工股份有限公司 | A kind of shallow mid-deep strata joint chromatography inversion speed modeling method of Depth Domain and system |
| CN108646288A (en) * | 2018-02-27 | 2018-10-12 | 中国石油天然气集团有限公司 | The method for building up and device of near-surface model |
| CN109085643A (en) * | 2018-07-30 | 2018-12-25 | 中国石油化工股份有限公司 | The early substep joint inversion method to wave |
| CN110954971A (en) * | 2018-09-26 | 2020-04-03 | 中国石油化工股份有限公司 | Method and system for establishing digital model containing shallow surface information |
| CN110954971B (en) * | 2018-09-26 | 2022-04-12 | 中国石油化工股份有限公司 | Method and system for establishing digital model containing shallow surface information |
| CN110967745A (en) * | 2018-09-29 | 2020-04-07 | 中国石油化工股份有限公司 | Depth domain velocity modeling method for igneous rock |
| CN109238310A (en) * | 2018-11-05 | 2019-01-18 | 珠海全志科技股份有限公司 | A kind of pair of MEMS sensor carries out the method and device of temperature-compensating |
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Inventor after: Hu Guanghui Inventor after: Wang Lixin Inventor after: Sun Jingmei Inventor after: Wang Jie Inventor after: He Jianbo Inventor after: Jia Chunmei Inventor after: Shen Zhongqiu Inventor after: Yin Li Inventor after: Wang Zhenyu Inventor before: Hu Guanghui Inventor before: Wang Lixin Inventor before: Sun Jingmei Inventor before: Wang Jie Inventor before: He Jianbo Inventor before: Jia Chunmei Inventor before: Shen Zhongqiu Inventor before: Yin Li Inventor before: Wang Zhenyu |
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