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- Volume 34, Issue 3, 2016
First Break - Volume 34, Issue 3, 2016
Volume 34, Issue 3, 2016
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Geomechanical analysis of in-situ stress and its influence on hydraulic fracturing at the Wattenberg Field, Colorado
Authors Travis Pitcher and Thomas L. DavisThe Reservoir Characterization Project, in conjunction with Anadarko Petroleum Corporation, undertook an integrated dynamic reservoir characterization of a portion of Wattenberg Field. We have examined various well completion parameters and their influence on production. Our conclusion is that little correlation exists between the completions parameters (fluid and proppant injection) and production. The largest control on production is geologic heterogeneity. We show that stress differences exist due to faults. Stress compartments subdivide the study area and account for localized stress rotations within fault-bounded blocks or compartments of the reservoir. These faults control stress distribution throughout the reservoir and are interpreted to be the main driving factors for production variability across the study area. Wattenberg Field is located northeast of Denver, Colorado (Figure 1). The field produces from sandstones, shales, and limestones of Cretaceous age. Discovered in 1970,Wattenberg Field has produced 321 million barrels of oil and 4.5 TCF of gas. More than 11,000 vertical wells are present in the field. Since 2007, horizontal drilling has been concentrated in the Niobrara and Codell intervals where both oil and gas are present (Figure 2). For a summary of the Niobrara/Codell resource play see Sonnenberg (2015). The Niobrara and Codell are the main development targets at depths of 6000 to 8000 ft (1800 to 2400 m). The Niobrara is comprised of approximately 300 ft (90 m) of interbedded limestone, chalks, and marls. The Codell Sandstone is a siltstone interval located below the base of the Niobrara and largely considered a separate reservoir interval.
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New methods for slicing and dicing seismic volumes
Authors Paul De Groot, Farrukh Qayyum, Yuancheng Liu and Nanne HemstraG lobal seismic interpretation techniques aim to arrive at fully interpreted seismic volumes. ‘Fully’ in this context, however, is misleading as it gives the impression that we are dealing with an end product and that there is no more interpretation to be carried out. This is not the case. The correlated geologic timelines of these volumes open up new ways to analyse seismic data, thereby increasing our understanding of the depositional history and improving our ability to find stratigraphic traps and to build accurate geologic models. Geologic information in global seismic interpretation techniques can be unlocked through new methods for dicing and slicing seismic volumes. Using HorizonCube, this can be achieved through attributes and a 3D Slider in a workflow that combines 2D and 3D visualization techniques with interactive analysis. Examples of such techniques will be introduced. The HorizonCube consists of a dense set of horizons that are computed from the seismic dip field. The vertical separation between horizons in a HorizonCube varies spatially. This feature is exploited in a new set of attributes called HorizonCube attributes that capture local and global information. Examples are: HorizonCube density and HorizonCube thickness attributes. Both attributes can be highly effective in the interpretation of unconformities, condensed sections and sedimentation rates. For slicing and dicing seismic volumes, we use a 3D Slider in a workflow that combines 2D and 3D visualization techniques with interactive analysis. The workflow enables scanning thousands of auto-tracked horizons rapidly with the objective to identify pairs of horizons corresponding to top and base of depositional features of interest. In the next step, isochron thicknesses or attribute responses are computed and geobodies are extracted.
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Diffraction imaging – a tool to reduce exploration and development risk
Authors N.R. Benfield, A. Guise and D. ChaseWhen evaluating exploration prospects, discoveries or a field under development it is essential to build an accurate structural framework at an appropriate scale. Detailed understanding of the fault network enables reservoir compartmentalisation risk to be better quantified at the exploration prospect stage and informs well placement optimisation in the exploration, appraisal and development phase. This paper presents a method for maximising fault information from depth migrated narrow azimuth seismic data. The faults are imaged in the depth domain by separating the diffracted component from the total migrated wavefield. We show that diffraction imaging gives higher resolution fault definition than either a conventional seismic reflectivity volume or conventional post-stack fault enhancement attributes. We also show that diffraction volumes can be further processed to generate attribute volumes with fault definition sharp enough to pick with automatic fault detection algorithms, producing a highly-detailed fault network that can augment manual fault interpretation products and be incorporated into the structural framework. Diffraction imaging is a technique for imaging small scale subsurface geological objects and discontinuities, such as faults, unconformities and karsts using the diffracted component of the total recorded wavefield.
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Generating maximum returns from reservoir modelling – increasing the upside potential of a mature Middle East field
By Samir WaliaT he decline in oil and gas prices and operators’ needs to generate maximum returns from their assets has ensured that reservoir modelling remains a powerful and highly important decision-making tool in the upstream oil and gas sector. 3D reservoir modelling is today the standard platform for the mapping, understanding and predicting of reservoir behaviour, providing operators with the crucial information they need on where to drill, what production strategies to adopt and how to maximize oil and gas recovery. By building a realistic representation of the geometry of the reservoir, operators can accurately map out fluid flows and volumes and make field development decisions that have a major impact on the field’s lifecycle and production capabilities for years to come. Yet, reservoir modelling can only be fully effective if it addresses potential bottlenecks in work processes and provides a seamless and integrated workflow across different domains. The danger of incomplete and inconsistent information being passed through the modelling chain, which ultimately forms the basis for field development decisions, is a considerable risk. From seismic interpretation through to the creation of a structural model, the incorporation of properties and dynamic uncertainties, and reservoir simulation and history matching, operators require a fully integrated uncertainty management workflow to protect investment returns and guide future development decisions. This article will illustrate how this has been achieved on a mature Middle East field, located in a highly tectonically active area. Figure 1 shows the field development plan.
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Anisotropy estimation based on the grey level co-occurrence matrix (GLCM)
A nisotropy refers to directional properties. In geophysics, we often refer to seismic anisotropy, the dependence of velocity on direction or upon angle (e.g., Crampin 1981, 1985; Lynn and Thomsen, 1990; Willis et al., 1986, Martin and Davis, 1987; Thomsen, 1986; Alkhalifah and Tsvankin, 1995). Variation in seismic velocity with direction may reflect lateral changes in facies, the presence of faults or fractures, or differences in pore fillings, among many factors that may influence velocity. In principal, seismic data can be used to estimate volumetric azimuthal anisotropy (Simon, 2005). In this work we focus on the application of textural attributes to estimate volumetric anisotropy. The grey level co-occurrence matrix (GLCM), initially described by Haralick et al. (1973) as a tool for image classification, is a measure of how often different combinations of pixel brightness values occur in an image. This method has widely been used for classification of satellite images (Franklin, et al., 2001; Tsai, et al., 2007), sea-ice images (Soh and Tsatsoulis, 1999; Maillard et al., 2005), and magnetic resonance and computed tomography images (Kovalev et al., 2001; Zizzari et al., 2011). This methodology can also be applied to seismic data to describe facies, reservoir properties, and fractures (Vinther et al., 1996; Gao, 1999, 2003, 2007, 2008a, 2008b, 2009, 2011; West et al., 2002; Chopra and Alexeev, 2005, 2006a, 2006b; Yenugu et al., 2010; de Matos et al., 2011; Eichkitz and Amtmann et al., 2012b, 2013, 2014, Eichkitz and de Groot et al., 2014; Eichkitz et al., 2015a, 2015b). GLCM–based attributes can be calculated in different directions, yielding an array of radial responses. By comparing these different results it is possible to determine anisotropy in the seismic data. Here, directional GLCM–based attributes are used for the description of channel structures and for the interpretation of fractured reservoirs.
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Low-frequency signal enhancement by pseudo-Vz deghosting
Authors Ekeabino Momoh, David Halliday, Ralf Ferber and Satish SinghWe examine the estimation of the vertical component of particle motion (‘pseudo-Vz’) data from deep-tow streamer pressure data. The estimated data is then combined with the pressure data to attenuate the pressure ghost by a procedure referred to as pseudo-Vz deghosting. The notches created by the destructive interference of the up- and down-going waves at the receivers are shown to be ‘filled’ with information about the upgoing waves, thereby improving the signal-to-noise ratio. In addition, it is shown that even though they may not be present in the input data, by including sparsity constraints in the deghosting process, coherent and energetic signals at the low-frequency part of the spectrum can be estimated using this technique. The enhanced signals at notch frequencies provide broadband data. The proposed technique can be used, for example, for future deep-tow marine seismic data acquisition benefiting from higher signal-to-noise ratio at greater streamer depth, as well as in re-processing of existing data, for example in a time-lapse scenario, making them more comparable to future broadband data. We demonstrate the technique on a 2D deep-tow marine seismic data set acquired along a transect on the Sumatra subduction zone, in southwest Indonesia.
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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)