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- Volume 39, Issue 3, 2021
First Break - Volume 39, Issue 3, 2021
Volume 39, Issue 3, 2021
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Tutorial: a geophysical perspective on machine learning
By Ian F. JonesAbstractMachine learning is fast becoming omnipresent in all aspects of science involving large volumes of data. The terminology and ideas involved are not immediately transparent or obvious to people not already immersed in the minutia of the implementation of machine learning procedures. Here, I try to relate the concepts and terminology used in machine learning to things that geoscientists will already be familiar with, so as to form a bridge between their current knowledge and an understanding of machine learning.
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Imaging and depth conversion of low relief fields
Authors Chris Field, Said Al Abri, Ahmed Obeidi and Tahira QureshiAbstractA huge proportion of the world’s known hydrocarbon accumulations reside in low-relief structures (see, for example, (Macgregor, 1996)). Capturing top-reservoir undulation for low-relief fields is crucial, impacting reserve calculations and development decisions. We present a workflow and case study of a greenfield development from onshore the Arabian Plate (Sultanate of Oman) where reprocessing and depth conversion velocity model building led to better characterisation of the reservoir and depth uncertainties. With the subtle structural variation captured in two-way-time, time-depth conversions based on direct velocity data allowed the team to make explicit examination of the consequences of the uncertainty to these low-relief reservoirs. In both the reprocessing and depth conversion, horizontal wells played a novel role in the quality control.
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Seismic classification: A Thalweg tracking/machine learning approach
Authors Paul de Groot, Mike Pelissier and Marieke van HoutAbstractWe describe a machine learning seismic classification workflow in which the thousands of class labels needed for training a deep graph are automatically generated from just a handful of manually picked seed positions. The class labels are generated by a Thalweg tracker. This special kind of connectivity filter grows a 3D body of user-defined size from a single seed position by adding only one point at a time. The user controls the size such that the tracker stays within one seismic class. The shape of the growing body is the main criterion for deciding when and where the tracker starts tracking another class. We present two examples. The first example is a 3D seismic facies classification of a setting with stacked meandering channels. We classify the target interval into eight seismic facies classes. In the second example, we extract turbidite channels from a two-pass gradient (i.e., second derivative) attribute volume.
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Velocity for inversion of 3D seismic surveys
By Huw JamesAbstractIn the paper ‘Revisiting Dix’s RMS Velocity’ (James, 2018) it was shown that there is no single velocity function that will accurately correct NMO for all the offsets in a seismic shot record. For the simplest possible model, with more than one layer NMO, velocity is not hyperbolic. Therefore, since the idea that ‘NMO velocities can be approximated by RMS averages of interval velocities’ is pervasive in seismic data processing we need some adjustment to our procedures. The impetus to study RMS velocities came from the practice of muting far offsets when performing AVA/AVO analysis and the far offsets were not flat in time after NMO. With the muting, the information at far offsets was discarded. Historically NMO velocities were picked directly and so it was never necessary to have reflections that were not flat after correction. Muting for NMO was restricted to the region where refractions and or reflections interfered with each other.
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The effects of lithology and facies types on the anisotropy parameters and upscaling factor of the sand reservoirs in the deep-water Sadewa field, Kutei Basin, East Kalimantan, Indonesia
AbstractThe anisotropy and upscaling factors adjustment are very important in the proper integration of the core ultrasonic and log sonic data for hydrocarbon reservoir characterization. Related to this issue, this paper evaluates the effects of the lithology and facies types on the anisotropy parameters and upscaling factor. The data are taken from the deep-water oil-gas Sadewa field located in the Kutei Basin, East Kalimantan, Indonesia at water depths of 500–750 m. The main reservoirs in this field are the Upper Miocene sand reservoirs deposited in the upper slope fan and channel facies. Fifty core plugs sampled at depths around 3000–4000 m were collected for thin-section petrography analysis and ultrasonic measurements. The thin-section petrography analysis shows that both facies areas are dominated by greywackes with parallel lamination structure and/or intergranular porosity. The 1 MHz ultrasonic velocities were measured in the 50 core plugs. Meanwhile, 10–40 KHz dipole sonic log data sampled at the same plug’s depth positions were used to calculate the elastic (Vp, Vs, Poisson ratio, etc) and Thomsen’s ε, γ and δ anisotropy parameters. The results show that for the parallel lamination and intergranular porosity greywacke samples, ε parameter is the best for compensating the anisotropy effect in the integrated core and log data reservoir quality determination (sand shale ratio, percentage of quartz contents, the effective and the total porosities). However, when the samples are non-intergranular porosity greywacke, the anisotropy effect in the core-log data correlation, is too irregular to be compensated by any elastic and anisotropy parameter. The core-log data upscaling factor in the channel facies is much smaller than the upper slope fan facies, and it is in line with the gamma-ray log data which indicates that the sandy channel facies is more homogeneous than the intercalated shale-sand upper slope fan facies. The overall results suggest that the lithology and facies types significantly affect the anisotropy parameters and upscaling factor. In addition, the best elastic or anisotropic parameters) should be determined to minimize the effects in the core and log data integration for hydrocarbon reservoir characterization.
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AVO modelling and interpretation with the help of the 1.5D elastic wave-equation
Authors A. Gisolf, P.R. Haffinger and P. DoulgerisAbstractIn this paper it is stated that, for the purpose of modelling and interpretation with the help of inversion, the elastic wave-equation is the correct way to link seismic data to the properties of the subsurface, through which the seismic waves are propagating. For Amplitude vs. Offset modelling/inversion the 1.5D data model is used and, therefore, also the elastic wave-equation is presented in this domain. The parameterization of the isotropic elastic wave-equation is directly in terms of elastic moduli, or compliances, which are closer to the desired reservoir properties than the conventional impedances. An iterative solution of the wave-equation is presented. It is demonstrated that the wave equation-based inversion contributes to increased interpretability, particularly in terms of hydrocarbon saturation of the reservoirs. Compared with the results from conventional linearized primary reflectivity-based inversion, it turns out that the wave equation-based method produces property results with a wider spatial bandwidth, due to the fact that it honours all internal multiple scattering and mode conversions generated over the target interval.
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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)