Application of multiparameter full-waveform inversion in Central Luconia Basin, Sarawak

2016 ◽  
Vol 4 (4) ◽  
pp. SU17-SU24 ◽  
Author(s):  
Vanessa Goh ◽  
Kjetil Halleland ◽  
René-Édouard Plessix ◽  
Alexandre Stopin
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Thin Layers ◽  
Earth Model ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Full Waveform ◽  
Velocity Variations ◽  
Central Luconia

Reducing velocity inaccuracy in complex settings is of paramount importance for limiting structural uncertainties, therefore helping the geologic interpretation and reservoir characterization. Shallow velocity variations due, for instance, to gas accumulations or carbonate reefs, are a common issue offshore Malaysia. These velocity variations are difficult to image through standard reflection-based velocity model building. We have applied full-waveform inversion (FWI) to better characterize the upper part of the earth model for a shallow-water field, located in the Central Luconia Basin offshore Sarawak. We have inverted a narrow-azimuth data set with a maximum inline offset of 4.4 km. Thanks to dedicated broadband preprocessing of the data set, we could enhance the signal-to-noise ratio in the 2.5–10 Hz frequency band. We then applied a multiparameter FWI to estimate the background normal moveout velocity and the [Formula: see text]-parameter. Full-waveform inversion together with broadband data processing has helped to better define the faults and resolve the thin layers in the shallow clastic section. The improvements in the velocity model brought by FWI lead to an improved image of the structural closure and flanks. Moreover, the increased velocity resolution helps in distinguishing between two different geologic interpretations.

The impact of acquisition geometry on full-waveform inversion updates

2021 ◽  
Vol 40 (5) ◽  
pp. 335-341
Author(s):  
Denes Vigh ◽  
Xin Cheng ◽  
Kun Jiao ◽  
Wei Kang ◽  
Nolan Brand
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Depth Image ◽  
Earth Model ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Full Waveform ◽  
Data Content ◽  
The Impact

Full-waveform inversion (FWI) is a high-resolution model-building technique that uses the entire recorded seismic data content to build the earth model. Conventional FWI usually utilizes diving and refracted waves to update the low-wavenumber components of the velocity model. However, updates are often depth limited due to the limited offset range of the acquisition design. To extend conventional FWI beyond the limits imposed by using only transmitted energy, we must utilize the full acquired wavefield. Analyzing FWI kernels for a given geology and acquisition geometry can provide information on how to optimize the acquisition so that FWI is able to update the velocity model for targets as deep as basement level. Recent long-offset ocean-bottom node acquisition helped FWI succeed, but we would also like to be able to utilize the shorter-offset data from wide-azimuth data acquisitions to improve imaging of these data sets by developing the velocity field with FWI. FWI models are heading toward higher and higher wavenumbers, which allows us to extract pseudoreflectivity directly from the developed velocity model built with the acoustic full wavefield. This is an extremely early start to obtaining a depth image that one would usually produce in much later processing stages.

Earth-model building from shallow to deep with full-waveform inversion

2016 ◽  
Vol 35 (12) ◽  
pp. 1025-1030 ◽  
Author(s):  
Denes Vigh ◽  
Kun Jiao ◽  
Xin Cheng ◽  
Dong Sun ◽  
Winston Lewis
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Earth Model ◽  
Full Waveform Inversion ◽  
Reflection Data ◽  
Full Waveform ◽  
Resolution Model ◽  
Data Content ◽  
High Resolution Model

Full-waveform inversion (FWI) is a high-resolution model-building technique that uses the entire recorded seismic data content to build the earth model. Conventional FWI usually utilizes diving and refracted waves to update the low-wavenumber/background components of the model; however, the update is often depth limited due to the limited offset range acquired. To extend conventional FWI beyond the limits of the transmitted energy, we must use reflection data. Synthetic and field data examples demonstrate that, even in a complex subsalt Gulf of Mexico setting, the background velocity model can be updated from shallow to deep water using conventional FWI followed by reflection-based FWI. A future refinement of the technique shows that, after updating the sediment model, the salt boundaries can be further updated by level-set technology.

Innovative application of full-waveform inversion applied to extended wide-azimuth marine streamer seismic in a complex salt environment

Geophysics ◽  
2022 ◽  
pp. 1-51
Author(s):  
Peter Lanzarone ◽  
Xukai Shen ◽  
Andrew Brenders ◽  
Ganyuan Xia ◽  
Joe Dellinger ◽  
...  
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Complex Salt ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Full Waveform ◽  
Velocity Model Building ◽  
Reservoir Systems

We demonstrated the application of full-waveform inversion (FWI) guided velocity model building to an extended wide-azimuth towed streamer (EWATS) seismic data set in the Gulf of Mexico. Field data were collected over a historically challenging imaging area, colloquially called the “grunge zone” due to the formation of a compressional allosuture emplaced between two colliding salt sheets. These data had a poor subsalt image below the suture with conventional narrow-azimuth data. Additional geologic complexities were observed including high-velocity carbonate carapace near the top of salt and multiple intrasalt sedimentary inclusions. As such, improved seismic imaging was required to plan and execute wells targeting subsalt strata. Significant improvements to the velocity model and subsalt image were evident with wide-azimuth towed streamer and later EWATS data using conventional top-down velocity model building approaches. Then, high-impact improvements were made using EWATS data with an FWI velocity model building workflow; this study represented an early successful application of FWI used to update salt body geometries from streamer seismic data, in which many past applications were limited to improving sedimentary velocities. Later petrophysical data verified the new FWI-derived model, which had significantly increased confidence in the structural and stratigraphic interpretation of subsalt reservoir systems below the grunge zone.

An offshore Gabon full-waveform inversion case study

2016 ◽  
Vol 4 (4) ◽  
pp. SU25-SU39 ◽  
Author(s):  
Bingmu Xiao ◽  
Nadezhda Kotova ◽  
Samuel Bretherton ◽  
Andrew Ratcliffe ◽  
Gregor Duval ◽  
...  
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Earth Model ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Velocity Model Building ◽  
Building Process ◽  
Model Building Process

Velocity model building is one of the most difficult aspects of the seismic processing sequence. But it is also one of the most important: an accurate earth model allows an accurate migrated image to be formed, which allows the geologist a better chance at an accurate interpretation of the area. In addition, the velocity model itself can provide complementary information about the geology and geophysics of the region. Full-waveform inversion (FWI) is a popular, high-end velocity model-building tool that can generate high-resolution earth models, especially in regions of the model probed by the transmitted (diving wave) arrivals on the recorded seismic data. The history of the South Gabon Basin is complex, leading to a rich geologic picture today and a very challenging velocity model-building process. We have developed a case study from the offshore Gabon area showing that FWI is able to help with the model-building process, and the resulting velocity model reveals features that improve the migrated image. The application of FWI is made on an extremely large area covering approximately 25,000 [Formula: see text], demonstrating that FWI can be applied to this magnitude of survey in a timely manner. In addition, the detail in the FWI velocity model aids the geologic interpretation by highlighting, among other things, the location of shallow gas pockets, buried channels, and carbonate rafts. The concept of actively using the FWI-derived velocity model to aid the interpretation in areas of complex geology, and/or to identify potential geohazards to avoid in an exploration context, is applicable to many parts of the world.

Full-waveform inversion for full-wavefield imaging: Decades in the making

2021 ◽  
Vol 40 (5) ◽  
pp. 324-334
Author(s):  
Rongxin Huang ◽  
Zhigang Zhang ◽  
Zedong Wu ◽  
Zhiyuan Wei ◽  
Jiawei Mei ◽  
...  
Keyword(s):  
Model Building ◽  
Seismic Imaging ◽  
Structural Information ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Data Types ◽  
Velocity Models ◽  
Full Waveform

Seismic imaging using full-wavefield data that includes primary reflections, transmitted waves, and their multiples has been the holy grail for generations of geophysicists. To be able to use the full-wavefield data effectively requires a forward-modeling process to generate full-wavefield data, an inversion scheme to minimize the difference between modeled and recorded data, and, more importantly, an accurate velocity model to correctly propagate and collapse energy of different wave modes. All of these elements have been embedded in the framework of full-waveform inversion (FWI) since it was proposed three decades ago. However, for a long time, the application of FWI did not find its way into the domain of full-wavefield imaging, mostly owing to the lack of data sets with good constraints to ensure the convergence of inversion, the required compute power to handle large data sets and extend the inversion frequency to the bandwidth needed for imaging, and, most significantly, stable FWI algorithms that could work with different data types in different geologic settings. Recently, with the advancement of high-performance computing and progress in FWI algorithms at tackling issues such as cycle skipping and amplitude mismatch, FWI has found success using different data types in a variety of geologic settings, providing some of the most accurate velocity models for generating significantly improved migration images. Here, we take a step further to modify the FWI workflow to output the subsurface image or reflectivity directly, potentially eliminating the need to go through the time-consuming conventional seismic imaging process that involves preprocessing, velocity model building, and migration. Compared with a conventional migration image, the reflectivity image directly output from FWI often provides additional structural information with better illumination and higher signal-to-noise ratio naturally as a result of many iterations of least-squares fitting of the full-wavefield data.

Full waveform inversion: early start of model building process to resolve the complex near surface model in the Exmouth sub-basin, North West Shelf Australia

2018 ◽  
Vol 58 (2) ◽  
pp. 884
Author(s):  
Lianping Zhang ◽  
Haryo Trihutomo ◽  
Yuelian Gong ◽  
Bee Jik Lim ◽  
Alexander Karvelas
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Surface Velocity ◽  
Image Point ◽  
Surface Model ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
North West ◽  
Full Waveform

The Schlumberger Multiclient Exmouth 3D survey was acquired over the Exmouth sub-basin, North West Shelf Australia and covers 12 600 km2. One of the primary objectives of this survey was to produce a wide coverage of high quality imaging with advanced processing technology within an agreed turnaround time. The complexity of the overburden was one of the imaging challenges that impacted the structuration and image quality at the reservoir level. Unlike traditional full-waveform inversion (FWI) workflow, here, FWI was introduced early in the workflow in parallel with acquisition and preprocessing to produce a reliable near surface velocity model from a smooth starting model. FWI derived an accurate and detailed near surface model, which subsequently benefitted the common image point (CIP) tomography model updates through to the deeper intervals. The objective was to complete the FWI model update for the overburden concurrently with the demultiple stages hence reflection time CIP tomography could start with a reasonably good velocity model upon completion of the demultiple process.

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