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- Volume 36, Issue 6, 2018
First Break - Volume 36, Issue 6, 2018
Volume 36, Issue 6, 2018
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Quantitative interpretation using conventional and facies-based pre-stack inversion — A thin dolomite reservoir case study in Cabin Creek Field, Williston Basin
Authors Paul El Khoury, Ehsan Zabihi Naeini and Thomas L. DavisAbstractCabin Creek Field, on the southwestern flank of the Williston Basin, is one of 14 hydrocarbon fields within Cedar Creek Anticline. The field was initially discovered in May 1953 and developed by Shell starting with primary production followed by water flooding beginning in the late 1950s. In 1999, Encore purchased Shell’s interests and focused on infill drilling. In 2010, Denbury Resources acquired Encore giving it the potential to undertake enhanced oil recovery operations in the Rockies. Production is from the Ordovician Red River, Silurian Stony Mountain, Interlake, and Mississippian Mission Canyon Formations.
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Solving imaging challenges in a deep-water, complex ooze regime: a case study from the Outer Vøring area, Norwegian Sea
Authors Sören Naumann, Øystein Korsmo and Grunde RønholtAbstractA high-resolution velocity model is required in order to produce an accurate image of the subsurface in any complex geological setting. In shallow water environments, diving wave and refraction-based FWI has been widely used to resolve small-scale features. However, the depth that can be updated is limited by the deepest turning point of the diving waves. In a deep-water environment the use of diving waves and refractions is generally limited by the lack of ultra-far offsets required to record a sufficient amount of refracted energy. Furthermore, diving wave and refraction-based FWI assumes a medium with increasing interval velocities at all depths of interest.
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Putting a price on carbon — a North American perspective
More LessAbstractIn 1988 James Hansen summarized 30 years of climate research to a committee of the US Senate: (1) The Earth is warmer in 1988 than at any time in the history of instrumental measurements, (2) The global warming is now sufficiently large that we can ascribe with a high degree of confidence a cause and effect relationship to the greenhouse effect, and (3) In our computer climate simulations the greenhouse effect now is already large enough to begin to affect the probability of occurrence of extreme events such as summer heat waves. Hansen was referring to the addition to Earth’s ambient greenhouse effect produced by the combustion of hydrocarbons for energy production. The dilemma posed by the emission of man-made greenhouse gases is summarized by a global thermostat (Figure 1): the production of abundant hydrocarbon energy results in an unwanted warming of the planet.
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Seismic identification and applications of methane hydrate as a future energy source
Authors Karyna Rodriguez, Neil Hodgson and Hannah KearnsAbstractMethane hydrate, or clathrate, is an ice-like substance consisting of methane and water that is stable at low temperature and under high pressure. It has a pentagonal dodecahedron molecular structure comprising one molecule of methane surrounded by molecules of water. It is usually found in areas with low temperatures, such as in the Arctic, in the form of methane hydrate deposits above and below the lower limit of permafrost. Hydrates are also common in deep water where the water column above 300 to 500 m water depth provides the high-pressure conditions required for their formation.
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Solving exploration problems with machine learning
Authors Deborah Sacrey and Rockey RodenAbstractOver the past eight years the evolution of machine learning in the form of unsupervised neural networks has been applied to improve and gain more insights in the seismic interpretation process (Smith and Taner, 2010; Roden et al., 2015; Santogrossi, 2016: Roden and Chen, 2017; Roden et al., 2017). Today’s interpretation environment involves an enormous amount of seismic data including regional 3D surveys with numerous processing versions and dozens if not hundreds of seismic attributes. This ‘Big Data’ issue poses problems for geoscientists attempting to make accurate and efficient interpretations. Multi-attribute machine learning approaches such as self-organizing maps (SOMs), an unsupervised learning approach, not only incorporates numerous seismic attributes, but often reveals details in the data not previously identified. The reason for this improved interpretation process is that SOM analyses data at each data sample (sample interval X bin) for the multiple seismic attributes that are simultaneously analysed for natural patterns or clusters. The scale of the patterns identified by this machine learning process is on a sample basis, unlike conventional amplitude data where resolution is limited by the associated wavelet (Roden et al., 2017).
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Back is the future: returning samples from Mars for analysis on Earth
By M.A. SephtonAbstractSeeking evidence of life in the solar system will be partly the search for organic signatures in rock matrices. The search for organic matter is common to petroleum exploration on Earth and life search missions to Mars. Despite some commonality between investigations into life records on Earth and Mars, there are also significant differences. Favourable organic concentrations in petroleum source rocks are much higher than those needed for life-search targets on Mars. Choosing samples for collection on Mars for return to Earth requires more care at earlier stages than needed for collection of samples on Earth. During and after collection, samples of Mars must be protected from organic contamination that could confuse their potentially weak and poorly understood signals. While operations on Mars provide effectively unlimited samples but with limited instrumentation, analysis on Earth involve constrained amounts of returned samples but access to the world’s best analytical capabilities. Returning samples from Mars also presents the potential for historical firsts including new technologies and important preparations for the eventual human exploration of the Red Planet.
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Geologically consistent multiphysics imaging of the Darajat geothermal steam field
AbstractDarajat is a vapor-dominated, producing geothermal field in West Java, Indonesia. Located along a range of Quaternary volcanic centres, it is associated with an eroded andesitic stratovolcano, and its reservoir is predominantly comprised of thick lava flows and intrusions in a stratovolcano central facies (Rejeki et al., 2010). First production from the field was started in 1994 with the installation of a 55 MW plant, and capacity was added in 2000 and 2007 to bring the total to 271 MW.
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Recent developments in object modelling opens new era for characterization of fluvial reservoirs
Authors Markus L. Vevle, Arne Skorstad and Julie VonnetAbstractFluvial depositional environments play a major role as hydrocarbons reservoirs around the world and have therefore received considerable attention in the domain of reservoir modelling (Keogh et al., 2007). Modelling of fluvial reservoirs represents a vast research field. The wide range of scales, the heterogeneity of deposits, the complex geometry has made them highly challenging to incorporate into subsurface models to replicate the reservoir behaviour in 3D.
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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)