Anisotropic Earth Model Building Using Multi-survey Full Waveform Inversion with Ocean-bottom Cable and Streamer Data

2017 ◽  
Author(s):  
L. Zhang ◽  
N. Zimmermann ◽  
A. Bullock ◽  
T. Khlussovich ◽  
Ø. Runde ◽  
...  
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Earth Model ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Full Waveform ◽  
Streamer Data

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.

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.

Accelerating Subsurface Data Processing and Interpretation with Cloud-Based Full Waveform Inversion Systems

2021 ◽  
Author(s):  
Sirivan Chaleunxay ◽  
Nikhil Shah
Keyword(s):  
Service Sector ◽  
Model Building ◽  
Job Scheduling ◽  
Waveform Inversion ◽  
Earth Model ◽  
Full Waveform Inversion ◽  
Spare Capacity ◽  
Velocity Models ◽  
Full Waveform ◽  
Job Scheduler

Abstract Understanding the earth's subsurface is critical to the needs of the exploration and production (E&P) industry for minimizing risk and maximizing recovery. Until recently, the industry's service sector has not made many advances in data-driven automated earth model building from raw exploration seismic data. But thankfully, that has now changed. The industry's leading technique to gain an unprecedented increase in resolution and accuracy when establishing a view of the interior of the earth is known as the Full Waveform Inversion (FWI). Advanced formulations of FWI are capable of automating subsurface model building using only raw unprocessed data. Cloud-based FWI is helping to accelerate this journey by encompassing the most sophisticated waveform inversion techniques with the largest compute facility on the planet. This combines to give verifiable accuracy, more automation and more efficiency. In this paper, we describe the transformation of enabling cloud-based FWI to natively take advantage of the public cloud platform's main strength in terms of flexibility and on-demand scalability. We start from lift-and-shift of a legacy MPI-based application designed to be run by a traditional on-prem job scheduler. Our specific goals are to (1) utilize a heterogeneous set of compute hardware throughout the lifecycle of a production FWI run without having to provision them for the entire duration, (2) take advantage of cost-efficient spare-capacity compute instances without uptime guarantees, and (3) maintain a single codebase that can be run both on on-prem HPC systems and on the cloud. To achieve these goals meant transitioning the job-scheduling and "embarrassingly parallel" aspects of the communication code away from using MPI, and onto various cloud-based orchestration systems, as well as finding cloud-based solutions that worked and scaled well for the broadcast/reduction operation. Placing these systems behind a customized TCP-based stub for MPI library calls allows us to run the code as-is in an on-prem HPC environment, while on the cloud we can asynchronously provision and suspend worker instances (potentially with very different hardware configurations) as needed without the burden of maintaining a static MPI world communicator. With this dynamic cloud-native architecture, we 1) utilize advanced formulations of FWI capable of automating subsurface model building using only raw unprocessed data, 2) extract velocity models from the full recorded wavefield (refractions, reflections and multiples), and 3) introduce explicit sensitivity to reflection moveout, invisible to conventional FWI, for macro-model updates below the diving wave zone. This makes it viable to go back to older legacy datasets acquired in complex environments and unlock considerable value where FWI until now has been impossible to apply successfully from a poor starting model.

scholarly journals A parameterization study for elastic VTI full-waveform inversion of hydrophone components: Synthetic and North Sea field data examples

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. R299-R308 ◽  
Author(s):  
Antoine Guitton ◽  
Tariq Alkhalifah
Keyword(s):  
North Sea ◽  
Waveform Inversion ◽  
Transversely Isotropic ◽  
Horizontal Velocity ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
S Wave ◽  
Data Set ◽  
Full Waveform ◽  
Streamer Data

Choosing the right parameterization to describe a transversely isotropic medium with a vertical symmetry axis (VTI) allows us to match the scattering potential of these parameters to the available data in a way that avoids a potential tradeoff and focuses on the parameters to which the data are sensitive. For 2D elastic full-waveform inversion in VTI media of pressure components and for data with a reasonable range of offsets (as with those found in conventional streamer data acquisition systems), assuming that we have a kinematically accurate normal moveout velocity ([Formula: see text]) and anellipticity parameter [Formula: see text] (or horizontal velocity [Formula: see text]) obtained from tomographic methods, a parameterization in terms of horizontal velocity [Formula: see text], [Formula: see text], and [Formula: see text] is preferred to the more conventional parameterization in terms of [Formula: see text], [Formula: see text], and [Formula: see text]. In the [Formula: see text], [Formula: see text], and [Formula: see text] parameterization and for reasonable scattering angles (<[Formula: see text]), [Formula: see text] acts as a “garbage collector” and absorbs most of the amplitude discrepancies between the modeled and observed data, more so when density [Formula: see text] and S-wave velocity [Formula: see text] are not inverted for (a standard practice with streamer data). On the contrary, in the [Formula: see text], [Formula: see text], and [Formula: see text] parameterization, [Formula: see text] is mostly sensitive to large scattering angles, leaving [Formula: see text] exposed to strong leakages from [Formula: see text] mainly. These assertions will be demonstrated on the synthetic Marmousi II as well as a North Sea ocean bottom cable data set, in which inverting for the horizontal velocity rather than the vertical velocity yields more accurate models and migrated images.

scholarly journals High Resolution Anisotropic Earth Model Building on Conventional Seismic Data Using Full Waveform Inversion: A Case Study Offshore Australia

2015 ◽  
Vol 2015 (1) ◽  
pp. 1-5
Author(s):  
Bee Jik Lim ◽  
Denes Vigh ◽  
Stephen Alwon ◽  
Saeeda Hydal ◽  
Martin Bayly ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Model Building ◽  
Waveform Inversion ◽  
Earth Model ◽  
Full Waveform Inversion ◽  
Full Waveform
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