Technical Library

  • Multi-azimuth multisensor quantitative interpretation: a South Viking graben case study, Norway

    Author: Cyrille Reiser, Eric Mueller
    First Break - 6 September 2021

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    The authors look at the reservoir characterization of a recently acquired and processed multi-azimuth multisensor survey in the prolific South Viking Graben, offshore Norway.

  • Seismic image de-noising with convolutional neural network

    Author: Elena Klochikhina, Sean Crawley, Nizar Chemingui
    IMAGE 2021 - 1 September 2021

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    Seismic images are often contaminated by migration noise. The noise attenuation process can take a lot of effort from the domain expert and, in many cases, it can be challenging to get the optimal result. In recent years it has been demonstrated that data-driven approaches can produce quality results with minimum effort. In digital image processing, convolutional neural networks (CNN) have gained a lot of popularity. When trained properly on carefully selected data, CNNs can potentially outperform traditional methods through task automation leading to the reduced turnaround time of processing projects. In this work,
    we propose to train a neural network, specifically a U-net architecture, to eliminate migration artifacts from seismic images. We explain the data preparation step and describe
    the model parameters and training process. Finally, we demonstrate the model performance on field data examples from three different geographical regions.

  • Multi-Azimuth Multisensor Quantitative Interpretation: A South Viking Graben Case Study, Norway

    Author: Cyrille Reiser, Tim Bird
    IMAGE 2021 - 1 September 2021

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    Extracting the most reliable, high quality elastic and reservoir properties from seismic in an effective manner has always been the quest for every geoscientist trying to build
    a reservoir model or to estimate the petroleum resources. This presentation will focus on the reservoir characterization of a recently acquired and processed multi-azimuth
    multisensor survey in the prolific South Viking Graben, offshore Norway. This area has delivered a number of significant successes in multiple plays over the past decade.
    We will focus our analysis on the quantitative interpretation of the various stratigraphic intervals ranging from the Tertiary to the Permian reservoir levels using this dataset
    integrated with the many wells present in and around the area of interest. From the well data, a company multi-client interactive regional rock physics modelling product has been used, enabling a rapid assessment of the elastic properties variation as well as the pre-stack seismic responses with changes of reservoir condition. This case study will highlight how this new dataset integrated with regional well information can overcome some of the exploration and nearfield exploration challenges. Even though the project work is still on-going, very promising results have been achieved for the evaluation of reservoirs and trapping styles of existing fields and discoveries as well as for the mapping of additional opportunities which would be of interest for any future near-field exploration activity.

  • Simultaneous inversion of velocity and reflectivity

    Author: Yang Yang, Jaime Ramos-Martinez, Dan Whitmore, Guanghui Huang, Nizar Chemingui
    IMAGE 2021 - 1 September 2021

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    We introduce an inversion approach to simultaneously invert for both velocity and reflectivity. The core of the inversion workflow is a novel wave-equation that provides the full acoustic wavefield, which is parameterized in terms of velocity and vector reflectivity. A key aspect is the separation of the low- and high-wavenumber components of the gradient based on inverse scattering theory, enabling the sensitivity kernels to update the velocity and the vector reflectivity, respectively. The estimation problem is essentially a multi-parameter inversion where the crosstalk trade-offs between the two parameters are minimized with scale separation. Our adjoint state-based inversion is equivalent to performing Full Waveform Inversion (FWI) and Least-Squares Reverse Time Migration (LS-RTM) using the full acoustic wavefield within the same framework. The final inverted reflectivity is an accurate estimate of the true earth reflectivity, compensated for acquisition and poor illumination effects, and with reduced image crosstalk from multiples. The new approach reduces the turnaround time of imaging projects by combining velocity model building (FWI) and imaging (LS-RTM) into a single inversion
    process with minimum data preprocessing from an inaccurate initial model. We demonstrate the benefits of our scheme using synthetic and field data examples.

  • FWI in extended domain using time-warping

    Author: Guanghui Huang, Jaime Ramos-Martínez, Yang Yang, Nizar Chemingui
    IMAGE 2021 - 1 September 2021

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    The automation of model building using Full Waveform Inversion (FWI) depends on the lowest frequencies available in the data and an accurate initial model to avoid cycleskipping. To overcome the cycle-skipping, a new class of FWI approaches extend the solution search in one or more dimensions. We present a new method that uses the time warping function as the extension in the data space. This function dynamically transports the recorded data to the synthetic data and is imposed to represent the actual physical time. The resulting FWI objective function enables the solution of two parameters, velocity model and timewarping extension, in a single optimization problem, which is solved by the Alternate Direction Method (ADM). The mapping function is found by Dynamic Time Warping (DTW) with an augmented cost function provided by the time-warping extension. The novel FWI objective function, allows automatic transition from a pure time-shift problem to a conventional FWI. We apply the new FWI method to both synthetic and field data to demonstrate its effectiveness starting from inaccurate initial models. Results show that the new FWI approach is able to build high-resolution models from very simple initial velocity models.

  • Framework and standalone applications of machine learning in seismic processing

    Author: Tony Martin, Bagher Farmani, Morten Pedersen, Elena Klochikhina
    IMAGE 2021 - 1 September 2021

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    Machine learning, and the variations thereof, have been around for a considerable time, perhaps as far back as the early 19th century with Bayes’ work on probability theory. It
    is then a bit of a surprise that these techniques have not made more headway in seismic processing, a data rich industry that should naturally suit greater automation using machine learning algorithms. Mathematical functions used in seismic processing are
    highly evolved and designed to improve the data quality by removing noise, correctly positioning data, or enhancing the data quality. The decade’s long development of these
    applications means they are extremely good at solving the challenges each one individually addresses. So how can machine learning help when the industry already
    has highly evolved and effective tools? There are two possible categories for applications, one to supplement the existing functions in a framework that enables greater autonomy, and the second to replace tools that are not as effective as they could be, allowing a greater diversity of testing-free applications (generalization). In both cases, the goal is improved data quality, faster. We present examples that might benefit seismic processing, as well as comment on the challenges faced with these methods.

  • Brazil Campos Case Study: Improved Operation Efficiency and Reduced Risks by Introducing State of the Art Barnacle Mitigation Tools

    Author: Trygve Skadberg, Christian Vasbø, Rune Tønnessen
    IMAGE 2021 - 1 September 2021

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    We describe a series of barnacle mitigation measures applied during a five-month towed-streamer seismic survey by the Ramform Titan in the Campos Basin, Brazil. The 14 x
    10000m streamer spread was an industry record and occurred during the period of the year recognized as the high season for barnacles in the area, and was frequently affected by challenging weather too. The high-capacity seismic vessel was equipped with a pilot system for coating streamers with a proprietary anti-barnacle coating, deployed the self-propelled streamer cleaning units common to all PGS operations, and was also supported by the Thor Frigg; a large support vessel (Figure 1) equipped with a proprietary fast-going underwater drone capable of deploying the self-propelled streamer cleaners without workboat operations. Collectively, these barnacle-mitigation efforts present a unique insight into the complementary solutions necessary for remote operations in the most challenging settings. Our experiences demonstrated the usefulness of those tools. The prototype anti-barnacle coating required no attention for
    eight weeks on the streamer fronts where barnacle growth can become problematic during periods of no workboat activity being possible. The underwater drone removed the
    weather factor that correspondingly limits barnacle cleaning with traditional workboat-based tools, and thereby prevented a full spread recovery. The collective anti-barnacle
    mitigations enabled the survey to be completed ahead of schedule, despite particularly challenging conditions. Workboat-related HSE exposure was also greatly reduced.

  • Estimation of the acoustic wavefield generated by a seismic vessel from towed streamer data

    Author: Stian Hegna
    IMAGE 2021 - 1 September 2021

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    Imaging the subsurface using passive data acquired with a towed streamer configuration is discussed in this paper. Instead of an active source, the acoustic wavefield generated
    by the seismic vessel is used for imaging the subsurface. The primary purpose of this work was to test the feasibility of estimating the wavefield emitted from the seismic vessel using data recorded by towed streamers and using this wavefield for imaging the subsurface. After a description of a method for estimating the acoustic wavefield generated by the seismic vessel from towed streamer data acquired without an active source, a data example from offshore Malaysia will be shown. The acoustic signals generated by the seismic vessel have been estimated from recorded hydrophone data. This estimation is limited to frequencies above 30 Hz since non-acoustic noise dominates over the weak acoustic signals generated by the vessel at lower frequencies. Results from imaging the passive data using the estimated acoustic signals from the seismic vessel are compared with imaging the subsurface based on seismic data acquired with airguns.

  • Maximizing Quality and Efficiency of Multisensor Streamer Seismic with an Ultra-wide Penta Source Configuration

    Author: Martin Widmaier, Julien Oukili, Carine Roalkvam, Nolwenn Halbert, Rune Tønnessen
    IMAGE 2021 - 1 September 2021

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    An ultra-wide penta source configuration was deployed in combination with a high-density multisensor streamer spread to address shallow exploration targets in the western part of the Norwegian Barents Sea in 2020. The total source separation was 315 m, and is the widest towed by a seismic vessel in a commercial project to date. The survey area was
    near the Loppa High discovery in water depths from 300 to 400 m. Target depths are as shallow as 600-700 m. The innovative acquisition configuration provided very dense
    spatial sampling and uniform coverage of the ultra-near offset class for high-resolution imaging of shallow exploration targets and geohazards. At the same time, the improved near offset sampling was achieved without compromising acquisition efficiency.

  • Seismic Surveys Have Little Impact on Demersal Fishes

    Author: Andrew Long
    Industry Insights - 30 August 2021

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    A large-scale three-year experiment recently quantified the impacts of exposure to a commercial seismic source on an assemblage of tropical demersal fishes targeted by commercial fisheries on the North West Shelf of Western Australia. Monitoring of the composition, abundance, behavior, and movement of the fishes was pursued in multiple before-after-control-impact and dose–response experimental frameworks using acoustic telemetry and underwater video. The multidisciplinary team of scientists, technical staff and industry experts found there were no short-term (days) or long-term (months) effects of exposure on the composition, abundance, size structure, behavior, or movement of this fauna. These multiple lines of evidence suggest that seismic surveys have little impact on demersal fishes in this environment.

    Elements of results from the published study are summarized and highlighted.