Free-surface multiple attenuation using inverse data processing in the coupled plane-wave domain

Geophysics ◽  
2009 ◽  
Vol 74 (4) ◽  
pp. V75-V81 ◽  
Author(s):  
Jitao Ma ◽  
Mrinal K. Sen ◽  
Xiaohong Chen
Keyword(s):  
Free Surface ◽  
Plane Wave ◽  
Data Processing ◽  
Synthetic Data ◽  
Primary Energy ◽  
Matrix Inversion ◽  
Data Matrix ◽  
Inversion Method ◽  
Multiple Attenuation ◽  
Invariant Embedding

Free-surface multiples contain a large amount of energy in the seismic data because of large reflectivity of the free surface. We propose a method for free-surface multiple attenuation by a simple muting in the inverse coupled plane-wave domain. Our method is based on inverse data processing and the well-known 2D invariant embedding technique. If the lateral variation in subsurface structure is smooth, the data are well compressed in the 2D coupled plane-wave domain, reducing computation costs and stabilizing the inversion procedure. Surface multiples and primaries are well separated in the inverse coupled plane-wave domain, and multiples can be eliminated by simple muting, which does not damage the primary energy. To reduce artifacts, wraparound, and noise introduced by the frequency-domain data matrix inversion, horizontal and vertical tapers are applied. A least-squares matrix inversion method is chosen to stabilize the inversion. Synthetic data examples show that plane-wave inverse data processing is stable and successful in attenuating free-surface multiples.

Free-surface multiple attenuation for blended data

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. V227-V233
Author(s):  
Jitao Ma ◽  
Xiaohong Chen ◽  
Mrinal K. Sen ◽  
Yaru Xue
Keyword(s):  
Free Surface ◽  
Seismic Data ◽  
Synthetic Data ◽  
Primary Energy ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Crosstalk Noise ◽  
Multiple Attenuation ◽  
Blended Data ◽  
Value Decomposition

Blended data sets are now being acquired because of improved efficiency and reduction in cost compared with conventional seismic data acquisition. We have developed two methods for blended data free-surface multiple attenuation. The first method is based on an extension of surface-related multiple elimination (SRME) theory, in which free-surface multiples of the blended data can be predicted by a multidimensional convolution of the seismic data with the inverse of the blending operator. A least-squares inversion method is used, which indicates that crosstalk noise existed in the prediction result due to the approximate inversion. An adaptive subtraction procedure similar to that used in conventional SRME is then applied to obtain the blended primary — this can damage the energy of primaries. The second method is based on inverse data processing (IDP) theory adapted to blended data. We derived a formula similar to that used in conventional IDP, and we attenuated free-surface multiples by simple muting of the focused points in the inverse data space (IDS). The location of the focused points in the IDS for blended data, which can be calculated, is also related to the blending operator. We chose a singular value decomposition-based inversion algorithm to stabilize the inversion in the IDP method. The advantage of IDP compared with SRME is that, it does not have crosstalk noise and is able to better preserve the primary energy. The outputs of our methods are all blended primaries, and they can be further processed using blended data-based algorithms. Synthetic data examples show that the SRME and IDP algorithms for blended data are successful in attenuating free-surface multiples.

Dip selective 2-D multiple attenuation in the plane‐wave domain

Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 264-274 ◽  
Author(s):  
Faqi Liu ◽  
Mrinal K. Sen ◽  
Paul L. Stoffa
Keyword(s):  
Plane Wave ◽  
Source Function ◽  
Real Data ◽  
Wave Theory ◽  
Geological Structure ◽  
Multiple Attenuation ◽  
Invariant Embedding ◽  
Free Data ◽  
Air Water Interface ◽  
Lateral Variations

In many geological settings, strong reflections at the air‐water interface contribute to most of the multiple energy in the recorded seismograms. Here, we describe a method for free‐surface multiple attenuation using a reflection operator model of a seismic record, derived using the well‐known invariant embedding technique. We implement this method in the 2-D plane‐wave domain, where lateral variation of the geological structure of the earth is taken into account by the coupling of different ray parameters. In situations where the lateral variations are smooth, the data are well compressed in the 2-D plane‐wave domain and the resultant bandlimited matrices significantly reduce the computation cost. One important feature of the proposed method is its flexibility, which allows for the removal of multiples from selected reflections. To generate multiple free data, wave‐theory‐based multiple attenuation methods attempt to estimate either the source function or the subsurface reflectivity. Our method takes advantage of both approaches, such that we initially predict multiple traveltime using the reflectivity approach and then seek a source function to predict the amplitudes. Synthetic and real data examples show that this method is stable and successful in attenuating the surface multiples.

Using even terms of the scattering series for deghosting and multiple attenuation of ocean‐bottom cable data

Geophysics ◽  
1999 ◽  
Vol 64 (2) ◽  
pp. 579-592 ◽  
Author(s):  
Luc T. Ikelle
Keyword(s):  
Free Surface ◽  
Seismic Data ◽  
Primary Energy ◽  
Ocean Bottom ◽  
Receiver Side ◽  
Direct Wave ◽  
Sea Floor ◽  
Multiple Attenuation ◽  
Marine Surface ◽  
Streamer Data

Inverse scattering multiple attenuation (ISMA) is a method of removing free‐surface multiple energy while preserving primary energy. The other key feature of ISMA is that no knowledge of the subsurface is required in its application. I have adapted this method to multicomponent ocean‐bottom cable data (i.e., to arrays of sea‐floor geophones and hydrophones) by selecting a subseries made of even terms of the current scattering series used in the free‐surface multiple attenuation of conventional marine surface seismic data (streamer data). This subseries approach allows me to remove receiver ghosts (receiver‐side reverberations) and free‐surface multiples (source‐side reverberations) in multicomponent OBC data. I have processed each component separately. As for the streamer case, my OBC version of ISMA preserves primary energy and does not require any knowledge of the subsurface. Moreover, the preprocessing steps of muting for the direct wave and interpolating for missing near offsets are no longer needed. Knowledge of the source signature is still required. The existing ways of satisfying this requirement for streamer data can be used for OBC data without modification. This method differs from the present dual‐field deghosting method used in OBC data processing in that it does not assume a horizontally flat sea floor; nor does it require the knowledge of the acoustic impedance below the sea floor. Furthermore, it attenuates all free‐surface multiples, including receiver ghosts and source‐side reverberations.

Simulation and analysis of the coherent-dispersion spectrometer for exoplanet detection

2021 ◽  
Vol 503 (2) ◽  
pp. 3032-3043
Author(s):  
Yinhua Wu ◽  
Shasha Chen ◽  
Pengchong Wang ◽  
Shun Zhou ◽  
Yutao Feng ◽  
...  
Keyword(s):  
Data Processing ◽  
Michelson Interferometer ◽  
Energy Utilization ◽  
Design Stage ◽  
Inversion Method ◽  
Fringe Visibility ◽  
Common Path ◽  
Data Processing Method ◽  
Detection Instrument ◽  
Performance Research

ABSTRACT The coherent-dispersion spectrometer (CODES) is a new exoplanet detection instrument using the radial velocity (RV) method. This attempts mainly to improve environmental sensitivity and energy utilization by using an asymmetric, common-path Sagnac interferometer instead of a traditional Michelson interferometer. In order to verify its feasibility and to choose the appropriate key parameters to obtain the optimal performance, research on data processing for the design stage of the CODES is performed by systematic simulation and analysis. First, the instrument modelling is carried out for further data analysis according to the principle of the CODES, and the reliability of the model is verified by experiments. Second, the influence of key parameters on fringe visibility is analysed systematically, which provides a certain reference for the choice of the key parameters. Third, the RV inversion method for the CODES is proposed and optimized according to the related analysis results so as to promote RV inversion precision. Finally, the recommended values for the key parameters of the CODES are given. The experimental results show that the data processing error of RV inversion is less than 0.6 m s–1 within the recommended range of key parameters. This indicates that the scheme of the CODES is reasonable and feasible, and that the proposed data processing method is effective and well matched with the instrument design.

REAL-TIME 2.5D INVERSION OF LWD RESISTIVITY MEASUREMENTS USING DEEP LEARNING FOR GEOSTEERING APPLICATIONS ACROSS FAULTED FORMATIONS

2021 ◽  
Author(s):  
Kyubo Noh ◽  
◽  
Carlos Torres-Verdín ◽  
David Pardo ◽  
◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Fault Plane ◽  
Synthetic Data ◽  
Field Measurements ◽  
Geological Structure ◽  
Inversion Method ◽  
Adaptive Finite Element ◽  
Resistivity Measurements ◽  
Lwd Resistivity

We develop a Deep Learning (DL) inversion method for the interpretation of 2.5-dimensional (2.5D) borehole resistivity measurements that requires negligible online computational costs. The method is successfully verified with the inversion of triaxial LWD resistivity measurements acquired across faulted and anisotropic formations. Our DL inversion workflow employs four independent DL architectures. The first one identifies the type of geological structure among several predefined types. Subsequently, the second, third, and fourth architectures estimate the corresponding spatial resistivity distributions that are parameterized (1) without the crossings of bed boundaries or fault plane, (2) with the crossing of a bed boundary but without the crossing of a fault plane, and (3) with the crossing of the fault plane, respectively. Each DL architecture employs convolutional layers and is trained with synthetic data obtained from an accurate high-order, mesh-adaptive finite-element forward numerical simulator. Numerical results confirm the importance of using multi-component resistivity measurements -specifically cross-coupling resistivity components- for the successful reconstruction of 2.5D resistivity distributions adjacent to the well trajectory. The feasibility and effectiveness of the developed inversion workflow is assessed with two synthetic examples inspired by actual field measurements. Results confirm that the proposed DL method successfully reconstructs 2.5D resistivity distributions, location and dip angles of bed boundaries, and the location of the fault plane, and is therefore reliable for real-time well geosteering applications.

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