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- Volume 40, Issue 11, 2022
First Break - Volume 40, Issue 11, 2022
Volume 40, Issue 11, 2022
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Machine Learning Assisted Seismic Interpretation: a Case Study of the Loppa High Area, Barents Sea
Authors Louis Dyer and Surender ManralAbstractThe interpretation of faults and horizons from seismic data forms a critical part of the geoscience workflow, enhancing our understanding of the subsurface and ultimately the chance of success in extracting hydrocarbons. The depiction of these vital seismic interpretations has long been restricted to conventional manual and semi-automatic techniques, which require geoscientists to work line by line over ever-expanding volumes of seismic data.
The advent of machine learning (ML) and cloud computing technology has revolutionised tasks across multiple industries, enabling the identification of patterns in large multi-factor datasets. In this case study, we predict fault locations using 2D U-Net architecture convolutional neural network (CNNs) and predict horizons by employing Radial Basis Functions (RBFs) and Neural Networks (NNs). We aim to demonstrate the gains in efficiency and geological insight found using ML technology as the bedrock of the seismic interpretation workflow, through the interpretation of a broadband seismic dataset from the Loppa High area, Barents Sea.
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Derisking Offshore Windfarm Installation by Sub-Seafloor Boulder Detection Based on Dedicated Seismic Diffraction Imaging
Authors Stefan Wenau, Benjamin Schwarz, Viola Bihler, Eric Boyer and Benedict PreuAbstractIn order to confront climate change and reach the ambitious goals set at COP 26, established renewable energy sources like wind and solar need to expand to new frontiers. For wind, the transition to offshore environments poses unique opportunities and challenges. While offshore wind farms promise more energy efficiency, their construction demands larger investments in foundations and infrastructure.
Glacial movement that transported material over the various epochs has resulted in a liberal distribution of problematic boulders in exactly the kind of areas now proving ideal for the deployment of wind farm technology. This is especially evident in large stretches of the Baltic, North Sea and North Atlantic on the east coast of North America where boulders, carried south through glacial movements during the ice ages, pose significant hazards for the construction of new offshore infrastructure.
To be able to carry out subsea construction work with reduced risk, a novel ultra-high-resolution (UHR) seismic measurement system has been developed by the Fraunhofer Institute for Wind Energy Systems IWES, Bremen, Germany, and the University of Bremen, Germany. The Manta Ray G1 that has been developed is specifically designed to detect and localize these small-scale objects in marine sediments with high accuracy using seismic diffraction imaging. As these boulders pose an obvious problem for the construction work it is the ability of the system to commit to dedicated object detection, e.g., for glacial boulders, integrated into a detailed ground model of the uppermost section of the subseafloor in challenging shallow-water regimes that offers a highly advantageous solution to the problem. The system uses a unique new survey methodology for the de-risking of offshore construction sites.
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Imaging the Subsurface Using Acoustic Signals Generated by a Vessel
By Stian HegnaAbstractThe acoustic wavefield originating from a vessel has historically not been considered as a source of signal in the imaging of marine seismic data and is therefore treated as a source of noise. In this work, the feasibility of acquiring seismic data without an active source and instead using the acoustic wavefield generated by a vessel for imaging the subsurface has been investigated. There are areas around the world where the use of active marine seismic sources is not permitted throughout the year, or only permitted during short time periods. In such areas, acquiring seismic data using the acoustic signals generated by a vessel as a source may be an alternative. Using a vessel as a seismic source may also offer a low cost and low impact 4D monitoring solution with an opportunity for much more frequent acquisition of time lapse data especially over permanent receiver installations. This work demonstrates that it is possible to obtain very high-resolution seismic images of the shallow subsurface by using acoustic signals generated by a vessel. This outcome is due to the broadband signals that the vessel generates combined with the fact that these signals are generated continuously while the vessel is moving, allowing for extremely dense source-side sampling along the vessel path.
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Simulating Large-Scale Streamer and OBN Acquisition over Subsalt Targets — an Example of Successful Remote Collaboration Between Survey Design and Survey Evaluation
Authors Dave Ridyard, Dave Monk, Damian Hite, Lars Zühlsdorff and Trond HauglandAbstractIn this article we look at how ray-based wavefront modelling can be used to evaluate competing acquisition techniques with significantly different illumination properties and associated acquisition cost. We compare subsurface illumination of complex sub-salt reservoirs typical of those found in the Gulf of Mexico for a variety of towed-streamer and full azimuth long offset ocean bottom node surveys. Single, dual and triple azimuth towed-streamer surveys are considered.
This project was accomplished using a new connector between ACTeQ’s survey design and optimization software and Norsar’s 3D modelling software. This project is an excellent example of competitors collaborating to better achieve a customer’s needs.
The project was also accomplished in a fully remote environment, and none of the authors were in the same city at any time during the project. Remote collaboration is becoming an increasingly effective low-carbon approach to complex challenges.
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Volumes & issues
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Volume 42 (2024)
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Volume 41 (2023)
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Volume 40 (2022)
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Volume 39 (2021)
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Volume 38 (2020)
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Volume 37 (2019)
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Volume 36 (2018)
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Volume 35 (2017)
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Volume 34 (2016)
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Volume 33 (2015)
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Volume 32 (2014)
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Volume 31 (2013)
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Volume 30 (2012)
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Volume 29 (2011)
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Volume 28 (2010)
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Volume 27 (2009)
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Volume 26 (2008)
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Volume 25 (2007)
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Volume 24 (2006)
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Volume 23 (2005)
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Volume 22 (2004)
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Volume 21 (2003)
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Volume 20 (2002)
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Volume 19 (2001)
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Volume 18 (2000)
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Volume 17 (1999)
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Volume 16 (1998)
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Volume 15 (1997)
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Volume 14 (1996)
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Volume 13 (1995)
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Volume 12 (1994)
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Volume 11 (1993)
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Volume 10 (1992)
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Volume 9 (1991)
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Volume 8 (1990)
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Volume 7 (1989)
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Volume 6 (1988)
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Volume 5 (1987)
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Volume 4 (1986)
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Volume 3 (1985)
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Volume 2 (1984)
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Volume 1 (1983)