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The Gippsland Basin in South-Eastern Australia has been producing hydrocarbons since the early 1960’s when several giant oil and gas fields were discovered. It can therefore be considered to be a mature area, where production rates have been declining for the last twenty years and, with diminishing reserves, new reservoirs are being sought to meet the energy supply needs in this region. Since the initial discoveries there has been limited seismic exploration in this area and recent developments in broadband imaging technology, tomography and Full-Waveform Inversion mean that the existing data sets can be significantly improved by reprocessing to help to regenerate this basin.

In deep-water depositional systems such as the slope canyon-turbidite channel system encountered on the continental slope, offshore West Nile Delta Basin, deterministic prestack seismic inversion followed by facies classification delineated thick-bedded and thin-bedded gas-sand reservoirs encased in bypassed stratigraphic traps and also delineated prospective areas for development.

Below is a case study of the ongoing work on the Monarb and Seagull reprocessing projects in the Central North Sea, with a focus on the use of legacy near field hydrophone recordings, 3D recursive MWD, wave equation deconvolution and AVO QC (In particular Vp/Vs and Lambda Rho QC attributes)

We show how to separate the seismic image into specular reflections and diffractions using dip-angle gathers. A North Sea example and a 4D example are used to show the efficacy of the algorithm. The 4D example shows a significant reduction in imaging noise.

While the benefits of vertical particle velocity measurements are well known for towed streamer receiver deghosting, in many cases high noise levels can cause practical issues. We describe an inversion-driven receiver deghosting approach which is jointly constrained by hydrophone data and prior wavefield separated data. Prior wavefield separated data can relate to an up-going or down-going wavefield, obtained by combining hydrophone and particle velocity data. Use of prior wavefield separation data provides the joint inversion with signal at hydrophone notch frequencies, as well as making it less sensitive to variations in the free surface datum than hydrophone-only inversion methods. The use of data domain sparseness constraints makes the approach practical as it may be applied to data without prior denoise. The proposed method is validated on synthetic and real data examples.

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Viridien's Outcome-as-a-Service results-based model for HPC and AI is centered around performance, with pricing is based on results, not usage. With your KPIs in mind, our experts work with you to provide a scalable, cost-effective cloud environment to meet your business objectives.

A primary motivator for users to turn to HPC resources in the cloud has been to provision temporary capacity for jobs that surge and exceed the available utilization of on-premises systems. While that is still a driver for consuming HPC cloud resources, an increasing number of complex, computationally challenging jobs are capable of being run entirely in the cloud, particularly with the focused approach taken by HPC-as-a-service (HPCaaS) cloud providers.

The northern North Sea is a very active oil and gas exploration region, where several commercial discoveries have been made over recent years. The Lower Cretaceous sands within the Agat Formation is a reservoir play that has been targeted for decades. The quality and distribution pattern of the sand within the Agat Formation varies over the area, making it challenging to map the Agat play. A high-quality regional dataset is a valuable tool for interpretation and attribute generation to map out and correlate the different Agat sand packages and fairways.