Technical Library

  • Santos Vision: Innovative Seismic Data Processing in a Super Giant Oil Basin

    Author: Hermann Lebit, Sriram Arasanipalai, Jeff Tilton, Pascal Ollagnon
    GeoExpro - 1 May 2019

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    PGS has rejuvenated its Santos portfolio and final products from the reprocessing effort are available now. Covering around 34,000 km2, the Santos Vision program delivers the most comprehensive and geologically conformable dataset to date, mitigating exploration risk in the prolific pre-salt play of the basin. The latest in broadband processing has been applied and the single data volume represents the largest Reverse Time Migration (RTM) and Kirchhoff prestack depth migration (KPSDM) successfully completed by the industry.Extension of the dataset to more than 60,000 km2 of full and seamless coverage is in progress. The recent application of PGS Least-Squares Migration (LSM) to a subset of the seismic data demonstrates a further uplift in image resolution that provides unprecedented resolution in post- and pre-salt imaging.

  • A full wavefield approach to marine survey planning

    Author: Chloé Lazizi, Stefan Jetschny, Morten Pedersen, Alba Ordoñez
    First Break - 1 May 2019

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    Conventional processing of 3D marine seismic data based on primary reflections can suffer from strong acquisition related footprint. The problem manifests as gaps in the data because the water bottom and shallow features lack full illumination in shallow water data. The phenomenon is most obvious at the water bottom and gradually heals with increasing depth. This degradation of the shallow image is particularly problematic for surveys that target geohazard evaluation. Furthermore, accurate and continuous water bottom information can be crucial for multiple removal techniques that are required for successful imaging of deeper targets (Brittan et al., 2011). Separated wavefield imaging is a technique that has been developed to image the subsurface using any order of sea-surface multiples (Whitmore et al., 2010). The method requires the separation of upgoing and downgoing wavefields using multi-sensor marine streamer recordings (Carlson et al., 2007). By considering sea-surface reflections, receivers act as virtual sources, which provide increased lateral illumination and angular diversity compared to primary only reflections (Figure 1). Lu et al. (2013) demonstrated that imaging with sea-surface multiples is a valuable tool, providing a continuous water bottom image by reducing the acquisition related footprint and gives improved resolution of shallow structures. Separated wavefield imaging can therefore be used to obtain high-quality images from data acquired using operationally efficient acquisition configurations.

  • Quantum Computing: The Next Big Thing for Oil Exploration?

    Author: Andrew Long
    PGS - 1 May 2019

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    Quantum computers exploit the peculiar behavior of objects at the atomic scale, and use the ‘qubit’ as the basic unit of quantum computing. A quantum computer (QC) with only 100 qubits would, theoretically, be more powerful that all the supercomputers on the planet combined, and a few hundred qubits could perform more calculations instantaneously than there are atoms in the known universe. A QC with 79 qubits has already been built. After discussing one of the most popular methods to build qubits, I then address the critical phenomena of superposition, entanglement and interference that allow quantum circuits built from qubits to be so powerful. Consideration is given to one possible way of building qubits with superconducting circuits, and how such devices may be programmed. A notable feature is that quantum algorithms work not by the use of brute force, but by exploiting underlying patterns than can only be seen from a quantum viewpoint. An apparent application to the oil industry is the potential for machine learning solutions to work with far deeper levels of data complexity.

  • Integrating FWI Models and Broadband Data for Elastic Property Generation, What is Appropriate?

    Author: Tony Martin, Cyrille Reiser
    EAGE/PESGB Workshop on Velocities - 4 April 2019

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    Full waveform inversion (FWI) produces high-resolution earth models, the use of which can improve seismic imaging. FWI can also help create absolute inversion products, by filling the low frequency spectral gap in the integration with amplitude seismic data. However, what frequency should be used for FWI to cost-effectively estimate absolute elastic properties remains an open question. We present analysis from a case study in the Norwegian Sea. Initially we demonstrate how imaging challenges have been overcome by the use of FWI and high-end imaging. Following this, we reveal there is a cost-benefit sweet-spot for the low frequency models from FWI and broadband seismic amplitude data in the generation of absolute seismic inversion products.

  • Deep Updates - Challenges and Solutions for FWI

    Author: Nizar Chemingui, Alejandro Valenciano, Tony Martin
    EAGE/PESGB Workshop on Velocities - 4 April 2019

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    Conventional velocity model building (VMB) in complex regimes, such as intra and subsalt data, requires time consuming manual intervention. It is a process that can produce unreliable models, leading to an increase in uncertainty for subsalt lead evaluation. We demonstrate an application of Full Waveform Inversion (FWI) to refine legacy velocity models generated by conventional VMB. We present our solution on a simultaneous long offsets (SLO) dataset from the Gulf of Mexico, acquired with dual-sensor streamers, which provided low frequency rich data. The SLO configuration recorded data with 16 km of offset, enabling both refractions and reflections to update the deeper parts of the velocity model. We employ an FWI velocity gradient that eliminates the migration isochrones. This provides support for the intra and subsalt model updates by removing the reflectivity imprint from the updated models. The FWI application successfully refined the geometry of the salt bodies including the base salt and the intrasalt enclosures. RTM images show a marked uplift, particularly for both the salt flanks and subsalt reflectors.

  • Use of a Robust Norm in Reducing FWI Uncertainty in the Presence of Cycle Skipping

    Author: Jamie Ramos-Martinez, Alejandro Valenciano, Nizar Chemingui, Tony Martin
    EAGE/PESGB Workshop on Velocities - 4 April 2019

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    Full Waveform Inversion (FWI) can create on an inaccurate model as a result of cycle skipping, if the initial model is not close enough to the true one, or there is insufficient low frequencies in the data. Furthermore, FWI model updates can be affected by a reflectivity imprint prior to the resolution of long-wavelength features. Imaging with the resulting incorrect model will create structural uncertainty, and will hamper an evaluation of potential
    prospects. Cycle skipping can be mitigated by using a robust norm for measuring the data misfit (W2-norm), instead of a traditional L2-norm. Used with a velocity gradient that removes the imprint of the reflectivity, we demonstrate an application to data resolving a high-velocity layer that was not present in the inital model. Corroborated by well data, the resulting earth model accurately reflects the subsurface, which, in turn, reduces uncertainty in the final structural image.

  • Sample Size Automation in a Pseudo-random Model Uncertainty Workflow

    Author: Tony Martin
    EAGE/PESGB Workshop on Velocities - 4 April 2019

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    Velocity model building (VMB) using tomography produces one credible realization of an earth model, which, in turn, generates one conceivable subsurface image. The inversion, by its nature, is highly non-linear, and can lead to uncertainty with a single model and image approach. Uncertainty can be quantified by using a model population, rather than a single realization. In this scenario, all models must equally explain the data by producing flat gathers from the inversion. Defining what is an appropriate sample size for a nonlinear system using a pseudo-random approach to model uncertainty is critical for cost and turnaround. We automate a real-time constraint on the expanding model population using statistical relevance to the attributes produced through the uncertainty process. Analysis using cumulative distribution functions (CDFs) of the deviation in the model population define an automated threshold. The sample size threshold is met when there is no additional statistical relevance for the output attributes; the process stops and the model uncertainty metrics defining spatial reliability of the data are output. We demonstrate this method on data from the North Sea.

  • Machine Learning and Related Applications to Seismic

    Author: Andrew Long
    Industry Insights - 1 April 2019

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    The seismic industry will adopt a diverse range of AI solutions to a diverse range of seismic problems in coming years; both to augment better decision making, and to significantly accelerate the cycle time of seismic projects.

    Computationally-demanding processes such as velocity model building and seismic imaging are obvious targets for the development of innovative ways to do things much faster. Using the example here of velocity model building, although neural network-based alternatives to full waveform inversion (FWI) have been most popular in the literature, it can also be demonstrated that stochastic modeling methods using highly efficient reflection tomography can delivery accurate results up to two orders of magnitude faster. What is clear is that this arena is in its infancy, and pragmatic implementations will more likely move success from inflated expectations to demonstrable success.

  • Subsalt exploration in shallow waters of the Republic of Congo

    Author: Pierre Le Barbanchon, Tony Martin, Mark Martin, Louis Andzouono, Jean Pierre Saba, Alain Richard N’Gouala Nzoussi
    First Break - 1 March 2019

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    The authors reveal new subsalt hydrocarbon potential on the Congo Shelf using modern broadband imaging techniques applied to multi-vintage seismic data.

  • Nearer, Denser, Longer

    Author: Martin Widmaier, Sören Naumann
    GEO - 1 March 2019

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    With a smarter solution for resolving mixed depth targets in the Barents Sea, PGS expects beds as thin as 8 m to be resolved for Realgrunnen Subgroup.