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- Volume 35, Issue 10, 2017
First Break - Volume 35, Issue 10, 2017
Volume 35, Issue 10, 2017
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Seismic uncertainty estimation in reservoir structural modelling
Seismic interpretation is an important step in the reservoir model building workflow, and involves mapping the main surfaces and faults to establish the structural framework of the studied reservoir. However, uncertainties are inherently related to the seismic data due to several factors, such as limited registered bandwidth, structural and stratigraphic complexities associated to the reservoir encasing rocks and overburden, to seismic acquisition and processing workflows, energy spreading, tuning effects and noise, among others. Another important source of uncertainty – which is seldom treated – is conceptual uncertainty introduced by the interpreter. Bond et al. (2007), for example, present different interpretations obtained from the same seismic image. Despite the nature of the sources, these effects must be addressed in order to predict their impact on subsequent reservoir modelling steps and volume calculations. MacDonald et al. (2009) provide a description of the uncertainties present in each step of the reservoir modelling process. Leahy and Skorstad (2013) present a new workflow to quantify the uncertainties in seismic interpretation and use this information in the further modelling steps. Leahy et al. (2014) use the horizon uncertainty information to enhance the quality of the surface mapping, and hence reduce ambiguity on the interpreted surface. However, irrespective of the advantages in correctly identifying and quantifying the level of uncertainty on the interpretation of geological surfaces, it remains a highly labour intensive and time-consuming activity. Many interpreters do not have the available time or expertise to perform a detailed inspection of their data. Furthermore, each interpreter may quantify uncertainty in subtly different ways, creating some difficulty when comparing reservoir interpretations. The result is that all too often uncertainty analysis is superficially performed or completely absent, impacting the economic evaluation of the prospects. In order to provide valuable uncertainty analysis as fast and as accurately as possible, a new methodology to quickly assess the uncertainty information based on seismic data has been developed. This methodology lets the interpreter construct an uncertainty map through a combination of seismic attributes and can be used as initial, or ‘a priori’, information to correctly discriminate the low and high-resolution regions that correspond to areas of major and minor uncertainties, respectively. This approach of building the uncertainty map and the details of each step are described in the next section.
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Application of the seismic quality factor versus offset and azimuth (QVOA) for fractured reservoir characterization
Authors Karla Cecilia Avila Vizuett and Thomas DavisFractures impact the permeability of a reservoir and their characterization is important because the presence of fractures determines the flow of hydrocarbons during production. Accurate modelling of the fracture network can help in optimizing the production of the reservoir. Fractures affect the amplitudes of seismic waves; therefore, seismic attenuation is used to determine their characteristics. Here, a new technique of seismic fracture characterization is employed. QVOA, which involves the evaluation of the seismic attenuation (Q) and its variation with offset (O) and azimuth (A). The QVOA method is a two-step process where seismic attenuation is computed first and then its variation is determined with respect to offset and azimuth. We compute seismic attenuation using four different techniques based on the spectral ratio and frequency-shift methods. The variation with respect to offset and azimuth is determined using an approximate method of sectors (ASM) and approximate truncate method (ATM). The QVOA method is similar to the AVOA method for PP-reflection (Rüeger, 1997) since it includes intercept (A), gradient (B) and fracture orientation.
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Claiming a place for Guinea Bissau on the hottest shelf margin on planet Earth
Authors Neil Hodgson and Karyna RodriguezThe recent glut of giant oil and gas hydrocarbon discoveries on the North West African coast (Figure 1) began in 2014 with the SNE-1 discovery by Cairn in Senegal. This play-making well targeted Albian sandstones and Aptian carbonates in a structural trap, at the eroded edge of the Early Cretaceous platform margin. There are a number of interesting play elements at work in this play that require definition so that a model can be extracted and reused elsewhere along the margin in the chase for analogue traps. Where we will end up is Guinea Bissau, Senegal’s southern neighbour, where the plays is as yet unexplored yet appears to have an even more promising potential, but first – SNE. The SNE discovery has been presented to the industry by operator and partners several times over the last few years, including a presentation at the recent HGS PESGB African conference by Wytze de Boer et al. of Cairn Energy (Geophysics of the SNE Field, Senegal, HGS PESGB 16th African Conference, 2017). It is hardly surprising that industry is interested in this discovery as, with current resource estimates exceeding 500mmbbls, this was the biggest discovery in the world in 2014 and a truly ground-breaking, basin opening innovation. Most remarkable was that the discovery was oil – bucking the global trend of discoveries that was otherwise suggesting we have fine tools to explore for big gas resources but struggle to find big oil. The Liza-1 (>2bn bbls oil) discovery in Guyana in 2016 put this concept firmly to bed, yet the SNE discovery is still one of the few giant oil resource additions drilled this century.
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Quantitative interpretation sensitivity to angle and frequency-dependent pre-stack time shift, amplitude and phase perturbations
Authors Matthew Whaley, Cyrille Reiser and Andrew LongAs discussed by Long (2017), marine ‘broadband’ signal processing flows typically incorporate a combination of free-surface deghosting, spectral shaping, and attenuation compensation. Overall, there are many opportunities to corrupt the phase content in an angle-dependent and frequency-dependent manner during any signal processing flow, and such risks may increase during aggressive ‘broadband’ flows. We conducted a synthetic modelling study to quantify and understand how angle-dependent time shifts, angle-dependent frequency variations, or frequency-dependent phase errors can impact the recovery of elastic impedance attributes using pre-stack simultaneous seismic inversion. All modelling and inversion was 2D in nature, included no noise considerations, and assumed the velocity model was perfectly understood.
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Geosteering in thin sandstones — planning and operating a duo-lateral well in the Mittelplate oilfield, offshore Germany
By F. BremerThe Mittelplate oilfield is located in the German Wadden Sea National Park about 8 km west of the coastline of Schleswig-Holstein and 100 km northwest of Hamburg. For 30 years DEA Deutsche Erdoel AG has operated the field together with Wintershall Holding GmbH as its partner. Some 37 million m³ (232 million bbl.) have been produced from middle Jurassic sandstone reservoirs until by 2017 with 21 producing wells from the Mittelplate island and seven extended reach wells from Dieksand land station. The Büsum Dogger 1 well discovered the field in 1966 and in 1980 and 1981 the wells Mittelplate 1, 2 and 3 confirmed Germany’s largest oil accumulation. In 1985 the construction of the worldwide unique drilling and production island Mittelplate started. The Mittelplate field has been producing since 1987 with a current daily production of 4000 m³. The German Wadden Sea was declared a national park in 1985 and in 2009 the entire Wadden Sea area was dedicated as a Unesco World Heritage Site. Therefore, the development of the field has been limited to the existing offshore structure – the existing artificial drilling and production island Mittelplate A. A concept of multi-lateral wells has been successfully to optimise the limited number of available slots and reservoir exposure per well.
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A statistical sensitivity method for CSEM — implications for petroleum exploration in the Barents Sea
Authors Erik Mårten Blixt, Vidar Storvoll and Richard OlstadThis paper describes a statistical method for determining the probability for hydrocarbon detection by Controlled Source Electromagnetic (CSEM) data. The method can be used to quantitatively estimate the reliability and predictability of CSEM results and the validity of a CSEM interpretation over a specific target with given geological parameters (e.g. porosity and clay content). Wells and case studies from the Norwegian Barents Sea are used to highlight how the uncertainty of the geological model affects CSEM interpretation. All types of geoscientific applications face challenges on how to handle uncertainties; CSEM sensitivity studies are no different. The proposed method constrains the uncertainties by first establishing a statistical resistivity model containing expected resistivity and other geological parameters, then running Monte Carlo simulations to generate target specific sensitivity plots. Finally, the reservoir properties, e.g. porosity and clay content, can be varied to quantitatively establish if CSEM can detect a potential hydrocarbon column. The most important aspect of this method is that the CSEM integration and interpretation is now strongly controlled by the geoscientist, who must provide the expected reservoir parameters and their uncertainties for each target or case study under evaluation.
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A ‘sense check’ method for incorporating seismic amplitude information into prospect risk (a tribute to Mike Bacon)
By Rob SimmA simple Bayesian formulation is proposed as the basis of a prospect risking method that updates an initial geological chance of success by incorporating seismic DHI (direct hydrocarbon indicator) information. The key parameter is the ratio (R) of the probabilities P(dhi|hc) and P(dhi|nohc) (i.e. the relative probability that the DHI effects are due to the presence of hydrocarbons). The model proposed is that R is directly related to the number of first order DHIs with a subsequent modification by calibration and quality factors. This provides an understandable tool, which enforces a degree of objectivity to the amplitude update process and can be employed by geologists and geophysicists readily in the risking discussion. It is shown that the methodology is consistent with published statistics of drilled amplitude prospects.
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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)