A migration imaging method using CGP stacked cylindrical waves

In view of the seismic exploration problem of thin sand reservoirs in the Songliao Basin, this paper puts forward a migration imaging method using CGP （common geophone point） stacked cylindrical waves. By this means, seismic data should be acquired from a midpoint shooting layout system with small shot-point spacing and small geophone interval. Using such seismic data, CGP gathers are first stacked to compose a cylindrical wave section. The cylindrical wave section is migrated and imaged by means of the ray path downward continuation of the down-going wave and the wave equation downward continuation of the upgoing wave. The results from the modeling analysis and the data processing of the TK8157 seismic line in the Songliao Basin shows that the proposed migration imaging method has higher seismic resolution and fidelity. Furthermore, the proposed method is proven to be more effective for discovering small sand bodies, small faults, stratigraphic pinch-outs, and so on.

A new method of migration imaging for MT data

Based on the study on electromagnetic field migration by Zhdanov, we have proposed an improved method for the weak points in the research. Firstly, the initial background resistivity should be determined by using 1-D inversion results. Then in the process of continuation, the results are corrected and calculated layer by layer by the iteration method, so that more exact resistivity can be obtained. Secondly, an improved algorithm for finite-difference equation is studied. According to the property of electromagnetic migration field, the algorithm is designed by means of grids varying with geometric progression in the longitudinal direction. Being improved by the techniques mentioned above, better results are obtained by the new method, which has been verified by both the theory model and practical data.

Migration images guided high-resolution velocity modeling based on fully convolutional neural network

Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results that are less physically interpretative.Here,the authors propose a new method that uses migration images as input,combined with convolutional neural networks to construct high-resolution velocity models.Compared to directly using pre-stack seismic records as input,the nonlinearity between migration images and velocity models is significantly reduced.Additionally,the advantage of using migration images lies in its ability to more comprehensively capture the reflective properties of the subsurface medium,including amplitude and phase information,thereby to provide richer physical information in guiding the reconstruction of the velocity model.This approach not only improves the accuracy and resolution of the reconstructed velocity models,but also enhances the physical interpretability and robustness.Numerical experiments on synthetic data show that the proposed method has superior reconstruction performance and strong generalization capability when dealing with complex geological structures,and shows great potential in providing efficient solutions for the task of reconstructing high-wavenumber components.

Prestack migration velocity analysis based on simplified two-parameter moveout equation

Stacking velocity V_（C2）,vertical velocity ratio γ_0,effective velocity ratio γ_（eff）,and anisotropic parameter x_（eff） are correlated in the PS-converted-wave（PS-wave） anisotropic prestack Kirchhoff time migration（PKTM） velocity model and are thus difficult to independently determine.We extended the simplified two-parameter（stacking velocity V_（C2） and anisotropic parameter k_（eff）） moveout equation from stacking velocity analysis to PKTM velocity model updating and formed a new four-parameter（stacking velocity V_（C2）,vertical velocity ratio γ_0,effective velocity ratio γ_（eff）,and anisotropic parameter k_（eff）） PS-wave anisotropic PKTM velocity model updating and process flow based on the simplified twoparameter moveout equation.In the proposed method,first,the PS-wave two-parameter stacking velocity is analyzed to obtain the anisotropic PKTM initial velocity and anisotropic parameters;then,the velocity and anisotropic parameters are corrected by analyzing the residual moveout on common imaging point gathers after prestack time migration.The vertical velocity ratio γ_0 of the prestack time migration velocity model is obtained with an appropriate method utilizing the P- and PS-wave stacked sections after level calibration.The initial effective velocity ratio γ_（eff） is calculated using the Thomsen（1999） equation in combination with the P-wave velocity analysis;ultimately,the final velocity model of the effective velocity ratio γ_（eff） is obtained by percentage scanning migration.This method simplifies the PS-wave parameter estimation in high-quality imaging,reduces the uncertainty of multiparameter estimations,and obtains good imaging results in practice.

Study on Wave Field Characteristics and Imaging of Collapse Column in Three-Dimensional Detection with Love Channel Wave Reflected outside the Working Face

The safety accidents caused by collapse column water diversion occur frequently, which has great hidden danger to the safety production of coal mine. Limited by the space of underground, the detection of collapse column on the outside of working face has been a difficult problem. Based on this, numerical simulation and imaging research were carried out in this paper. The results indicate that when a seismic source near the roadway is excited, a part of seismic wave propagates along the roadway direction, namely direct P-wave, direct S-wave and direct Love channel wave. When the body waves and Love channel wave propagating to the outside of working face meet the interface of collapse column, the reflected Love channel wave and reflected body waves are generated. Reflection body waves and direct waves are mixed in time domain, which is difficult to identify in seismic records, while reflected Love channel wave whose amplitude is relatively strong. The reflected Love channel wave which has a large interval from other wave trains in the time domain is easily recognizable in seismic record, which makes it suitable for advanced detection of collapse column. The signal-to-noise ratio of X component is higher than that of Y component and Z component. According to the seismic records, polarization filtering was carried out to enhance the effective wave, which removed the interference waves, and the signal was migrated to get the position parameters of collapse column interface, which was basically consistent with the model position.

An amplitude-preserved adaptive focused beam seismic migration method

Gaussian beam migration （GBM） is an effec- tive and robust depth seismic imaging method, which overcomes the disadvantage of Kirchhoff migration in imaging multiple arrivals and has no steep-dip limitation of one-way wave equation migration. However, its imaging quality depends on the initial beam parameters, which can make the beam width increase and wave-front spread with the propagation of the central ray, resulting in poor migration accuracy at depth, especially for exploration areas with complex geological structures. To address this problem, we present an adaptive focused beam method for shot-domain prestack depth migration. Using the infor- mation of the input smooth velocity field, we first derive an adaptive focused parameter, which makes a seismic beam focused along the whole central ray to enhance the wave- field construction accuracy in both the shallow and deep regions. Then we introduce this parameter into the GBM, which not only improves imaging quality of deep reflectors but also makes the shallow small-scale geological struc- tures well-defined. As well, using the amplitude-preserved extrapolation operator and deconvolution imaging condi- tion, the concept of amplitude-preserved imaging has been included in our method. Typical numerical examples and the field data processing results demonstrate the validity and adaptability of our method.

Application of Two Migration Methods for Ground Penetrating Radar Data

This paper begins with the basic principles of finite-difference migration and diffraction scan migration, and then compares the processing results of the practical ground penetrating radar GPR data with these two migration methods. It is illustrated that migration can refocus the reflecting points in radar record to their true spatial location and provide the foundation for interpretation, thus improving precision of interpretation of (GPR) profiles. Key words finite-difference wave equation migration - diffraction scan migration - GPR - migration image CLC number TN 715.7 Foundation item: Supported by the National Natural Science Foundation of China (50099620) and the National High Technology Development 863 Program of China (2001AA132050-03)Biography: Shi Jing (1979-), female, Master candidate, research direction: signal processing

Migration of Magnetotelluric Data in Two——Dimensional Model

Since the wave equation of magnetoteiluric (MT)field is similar to the one of seismic , the migration techniques used in seismic can be applied to MT data . In this paper we make use of the principle of reflector mapping (i. e. U/D imaging principle ) to image MT data . That is, the MT wavefield observed on the surface of the earth can be resolved into upgoing and downgoing waves , the waves are extrapolated downward by the phase - shift method or the phase - shift plus interpolation (PSPI )method . Conductivity interfaces of the medium could be found by using the time coincidence of the upgoing and downgoing waves . Theoretical calculations show that the migration technique of MT data presented here is very effective . It can not only enhance the lateral resolution of MT data , but also obtain the visual image of subsurface interfaces . As compared with the conventional 2 - D inversion , this procedure is more simple in calculation and can be easily put into practice on a personal computer and is able to obtain the MT depth section , which is similar to seismic section .

Separation of diffracted waves via SVD filter

Diffracted seismic waves may be used to help identify and track geologically heterogeneous bodies or zones.However,the energy of diffracted waves is weaker than that of reflections.Therefore,the extraction of diffracted waves is the basis for the effective utilization of diffracted waves.Based on the difference in travel times between diffracted and reflected waves,we developed a method for separating the diffracted waves via singular value decomposition filters and presented an effective processing flowchart for diffracted wave separation and imaging.The research results show that the horizontally coherent difference between the reflected and diffracted waves can be further improved using normal move-out(NMO) correction.Then,a band-rank or high-rank approximation is used to suppress the reflected waves with better transverse coherence.Following,separation of reflected and diffracted waves is achieved after the filtered data are transformed into the original data domain by inverse NMO.Synthetic and field examples show that our proposed method has the advantages of fewer constraints,fast processing speed and complete extraction of diffracted waves.And the diffracted wave imaging results can effectively improve the identification accuracy of geological heterogeneous bodies or zones.

3-D Tunnel Seismic Advance Prediction Method with Wide Illumination and High-Precision

Tunnel seismic advance prediction can effectively reduce the construction risk during tunnel excavation.Compared with the 2-D method,the 3-D method is more conducive to describing the spatial characteristics of the geological body by adding the seismic data in the vertical direction.However,some drawbacks still need improvement in the current 3-D tunnel seismic prediction method.(1)The geometry is complex,which is destructiveness,high cost,and time-consuming,and will delay the tunnel construction schedule.(2)Illumination of the anomalous body is insufficient,and the precision of migration imaging is low.(3)Shot points are far away from the tunnel face,the energy loss at the shot points is more serious.(4)The received signals at the tunnel wall have the surface wave with strong energy when the shot points are placed on the tunnel wall.(5)The geometry is not linear,so the directional filtering method cannot be used to extract the reflection wave.To overcome the drawbacks of the current prediction method,a new 3-D symmetrical tunnel seismic prediction method is proposed.Six geophones are installed on the tunnel wall,two on the left side,two on the right side,and two on the top side.Twenty-four shot points are placed on the tunnel face and near both sides of the tunnel wall,twelve shot points on the left side and twelve shot points on the right side.The shot points will move along with the forward excavation of the tunnel.The wavefield analysis,illumination statistics,and 3-D reverse time migration imaging are used to evaluate the proposed method.The result of modeled data indicates that the proposed 3-D geometry has some advantages:(1)the geometry is simple and the geophone installation time is short;(2)it has high illumination energy,wide illumination range,and can improve the prediction distance and imaging accuracy;(3)the proposed 3-D method can better estimate the velocity of surrounding rock and is more conducive to extracting the reflection wave with high resolution.

Reflection full waveform inversion

Because of the combination of optimization algorithms and full wave equations, full-waveform inversion(FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data.Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI.