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- Volume 34, Issue 10, 2016
First Break - Volume 34, Issue 10, 2016
Volume 34, Issue 10, 2016
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A workflow to model anisotropy in a vertical transverse isotropic medium
Authors M. Reza Saberi and Jimmy TingVelocity anisotropy, which is known as the directional dependency of velocities, is becoming increasingly important in subsurface imaging and characterization. Most elasticity theories consider an isotropic medium to describe the phenomena in the field of reservoir geophysics. This assumption is challenged by the reality of the subsurface which is subject to a complex geological history such as tectonic movements and changes in the differential stress that can typically introduce fractures. In some cases, these factors can make the subsurface highly anisotropic. In general, four classes of anisotropy can be defined, ranging between the two extremes of a completely isotropic medium (with two elastic constants) and a completely anisotropic medium (with 21 elastic constants). The four classes refer to specific conditions where we can reduce the number of elements of the elastic stiffness tensor. These are known as Cubic (with three independent elastic constants), Transverse Isotropic or TI (five independent elastic constants), Orthorhombic (nine independent elastic constants) and Monoclinic (13 independent elastic constants). TI is the most often used to describe sedimentary rock. Anisotropy as an extension to isotropic approaches is usually dealt with using Thomsen (1986) parameters as approximations. Thomsen (1986) suggested three parameters to correct for anisotropy effects in weakly anisotropic media. These parameters, ε, δ and γ, are regularly used in all reservoir geophysics disciplines to address anisotropy effects. However, determining these three parameters is not straightforward and requires information such as laboratory data or well logs acquired in boreholes in different directions with respect to the symmetry axis of the anisotropy. The purpose of this paper is to review anisotropy in vertically isotropic media and use existing theory to model changes in the elastic stiffness tensor based on conventional well logs. Furthermore, this elastic stiffness tensor can be used to calculate the Thomsen parameters or even to model anisotropic velocities directly.
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Petroleum geologists and engineers: bridging the ‘two cultures’
More LessI n 1959, the noted British scientist and novelist C.P Snow titled his Rede Lecture at the University of Cambridge The Two Cultures. Snow argued that the intellectual life of the modern world is split into ‘two cultures’, namely the sciences and the humanities, and that the wide gap between these two is a major hindrance to solving the world’s problems. Snow’s book with the same title became a bestseller and the title itself has become a household name. Indeed, we also find ‘two cultures’ within the sectors of a given enterprise. In the petroleum industry, for example, we sometimes hear of the cultural differences between the upstream and the downstream, between the geologists and the engineers, or even among the geoscientists (geologists, geochemists and geophysicists) and among the engineers (reservoir, drilling, and production). I have even heard of the subtle differences between geological engineers and engineering geologists! Having different mindsets and training backgrounds is unavoidable, necessary and even desirable for the performance of our jobs. However, if our mindset becomes too closed, then we function in a trap and cannot see our blind spots; or even worse, we cannot communicate and work with our colleagues in the other fields of the industry. Therefore, while maintaining our expertise and standpoint is necessary, keeping an open-mind and striving to understand the other perspectives and fields of knowledge are equally important. After all, nature is not divided into various disciplines, departments or business units, but that the natural world with its resources is an interconnected whole. The petroleum industry functions on both geoscience and engineering (Figure 1). Dialogue, openness, and learning from each other’s culture indeed improve the performance of the industry and save financial resources as well. I have worked for both the oil industry and academia, and, in recent years, I have taught a graduate course on petroleum geoscience for engineers, which has provided me a wonderful opportunity to see the bridges between petroleum geoscience and engineering, and how the geoscientist and the engineer can learn from each other. An important point here is that we should not generalize our statements about either group, nor should we let our notions and impressions turn into prejudice. Therefore, rather than splitting my discussion into geology vs. engineering, I highlight four important points that we all, whether geologists or engineers, need to keep in mind in our work and interactions.
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A long-term seafloor deformation monitoring campaign at Ormen Lange gas field
Authors Shaun Dunn, Paul Hatchell, Annemieke van den Beukel, Robin de Vries and Tomas FrafjordSeafloor deformation monitoring is a new technology concept for offshore reservoir monitoring. Complementary to other areal monitoring techniques, it has the potential to cheaply and continuously monitor production induced changes in the reservoir and overburden. At Ormen Lange, Norway´s second largest gas field, a small trial network was deployed on the seafloor in 2007, followed by a full-field network in 2010. The network was operational for 5½ years before being retrieved in 2016. This article describes the technology, planning and execution of the survey at Ormen Lange, and findings from the data.
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The consequences of ignoring rock properties when predicting pore pressure from seismic and sonic velocity
Authors Edward Hoskin and Stephen O'ConnorRock properties are shaped by the geological history of the basin into which they have been deposited. The environment of deposition (and eroded hinterland provinces) controls the mineralogy and resultant rock type, while geological processes such as uplift, denudation, or constant deposition and burial will all shape the development of porosity in rocks. These factors may all play a part, to some degree, in the development of any abnormal pressure (herein termed overpressure; pressure in excess of the hydrostatic pressure) within formations. The more processes that have occurred, the more complicated the task will be to accurately predict this anomalous pressure. Typically, velocity data such as seismic interval velocity and sonic logs are used with industrystandard algorithms in all geological settings and lithology types to predict pore pressure. This paper will set out why standard pore pressure algorithms must only be applied after the rock properties have been assessed fully and examples are given of the circumstances where velocity data, both sonic and seismic, may never allow an accurate pressure assessment. Brief mention will also be made of why additional care must be taken before using seismic velocity to predict pore pressure.
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Quantifying the uncertainty of Gross Rock Volume: a decade of time-to-depth conversion in Sepat Field, Malay Basin
Authors Afiqah Radzi, Yusma Bazleigh and Ashraf KhalilGross Rock Volume (GRV) range and uncertainty estimation from depth maps is important for resource assessment, and represents a significant contribution from seismic interpretation into the reservoir model. Subsurface uncertainty comes from different factors such as errors in time and depth maps, number of wells drilled, property and facies modelling. This paper focuses on the sensitivity of GRV to various velocity models as the implementation of seismic technologies changed from 2002 to 2013 and as conventional time-to-depth migrated multi-component data was used for depth conversion. GRV estimates from different depth maps are captured and utilized for volumetric and structural uncertainty analysis. Sepat Field was discovered in 1983 and has been interpreted structurally as a 30 km long by 10 km wide, E-W trending, four-way dip closure dissected by normal faults. Like many of the oil and gas fields in the Malay Basin, it is significantly affected by shallow gas clouds especially in the crestal area of the structure (Figure 1). Shallow gas clouds cause amplitude and frequency attenuation and time structure sagging effects which lead to significant uncertainties in structural and stratigraphic mapping of reservoirs below the shallow gas area, and subsequently in the hydrocarbon resource assessment of these fields (Ghazali, 2013). A decade of various seismic vintages and studies are applied to the field in order to achieve better and more accurate depth predictions and quantify uncertainty. As a solution to the shallow gas cloud issue, a 4C seismic survey was acquired in 2012 with the objective of recording both compressional and mode converted shear wave (PS). Acquisition and Processing of PS mode conversions enables improvement in subsurface imaging and subsequent reservoir characterization (Barkved et al., 2004).
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Velocity model building and imaging in the presence of shallow gas
Authors A.R. Ghazali, R.J.J. Hardy, T. Konuk, R.I. Masiman, K. Xin, M.H. Mad Zahir and M.F. Abd RahimMultiple shallow layers of low saturation gas charged sands cause poor seismic imaging and hamper exploitation of many oil and gas discoveries in SE Asia. These gas ‘clouds’ are characterized by bright high amplitude reflectors of low P-wave velocity beneath which the seismic reflections have delayed P-wave travel times, reduced bandwidth, reduced reflected and transmitted amplitudes and associated phase distortion (Figure 1). All gas clouds are not equal, the appearance of gas clouds varies worldwide and within regions. A single gas-charged sand may sometimes have almost no effect on P-wave propagation; a shallow region of limited spatial extent may sometimes be undershot resulting in an interpretable image or multiple shallow layers can result in complete ‘wipeout’ of the final image. We believe that both anelastic losses and multiple scattering phenomena (indicated by rays on Figure 1) contribute to weak reflected energy beneath the gas-charged sands. A similar problem in the North Sea led to the development of multi-component seabed seismic solutions utilizing converted waves to penetrate beneath the gas (Berg et al., 1994). These solutions have been successfully applied to the largest of the Malaysian producing fields and are the PETRONAS preferred technical solution (e.g. Radzi et al., 2015). As with many problems, a mixture of acquisition and processing related solutions produces the optimal result but sometimes processing alone can produce a cost-effective result. Despite cost reductions and technical advances, converted wave imaging is still expensive, difficult and time consuming. In this paper we attempt to build an efficient and accurate workflow for velocity model building of P-wave data in order to best exploit the latest imaging algorithms. We use a mixture of synthetic and real data examples from offshore Malaysia to illustrate this difficult and unresolved problem.
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Improved depth conversion with FWI – a case study
Authors A.J. O'Neill and T.A. ThompsonIn the study region, notoriously heterogeneous shallow carbonates, here between depths of approximately 1.5- 2.5 km, give rise to short-wavelength velocity variations in the overburden, which can cause severe depth undulations at the reservoir level (~3 km depth subsea). As the reservoirs are relatively thin (~30 m), stacked, fluvial-deltaic channel sands with sharp meanders and lateral truncations, even a localised 1% velocity error can produce a 30 m depth error at 3 km, which is not acceptable for development well planning. The resolution of traveltime-tomography is limited and may not resolve overburden variability in a manner suitable for depth conversion in a development setting. Geostatistical scaling using the available well control is one option to further improve depth conversion reliability. This workflow utilizes time-depth data at well locations along with geophysically constrained statistics to derive a stable, geologically plausible background trend that accounts for the majority of depth error. The result is a regionally consistent model that ties the available well control and provides more reliable depth conversion away from wells. The background trend provided by the well-based velocity calibration is however a long-wavelength solution and is unlikely to be able to correct for the short-wavelength depth errors which can arise at depth. FWI on the other hand provides a resolution of less than half a seismic wavelength to capture thin and localized subsurface features. With short-wavelength features accurately resolved, well control can then be used to correct for any residual long-wavelength errors and ensure more reliable depth conversion away from the wells. In this study, reflection tomography and 3D TTI (tilted transverse isotropy) FWI velocity models were geostatistically calibrated to wells and compared for depth conversion accuracy. Using the calibrated reflection tomography model, early appraisal wells were still more than 50 m off prognosis at the top reservoir level. These appraisal wells were just a few hundred metres away from the exploration wells used for control. 3D TTI FWI was then run using the reflection tomography model as input. The same geostatistical calibration to wells was applied to the FWI output and ultimately provided a model with depth conversion accuracy to within 15 m at the reservoir level.
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Velocity model building challenges and solutions in a SE Asian basin: beyond reflection tomography
Brunei Darussalam, on the South-East Asian island of Borneo, has a long history of oil and gas production. Oil was first discovered in the onshore Seria field in 1929. Other sizeable fields have been discovered since, such as Champion and Ampa, and a high level of exploration and development activities are continuing. To ensure the challenges that come with these activities can be addressed adequately, a large part of Brunei’s offshore has recently been covered by modern broadband acquisition. Remaining parts offshore are covered by older 3D seismic. The coastal strip of Brunei, encompassing among others the large Seria field, is covered by wide-azimuth 3D land and transition-zone data. Brunei’s subsurface geology poses some specific challenges for seismic imaging for hydrocarbon exploration and development purposes. Shallow gas accumulations – gas clouds or gas bags – absorb much of the seismic energy and cause a wipe-out zone below them. Many exploration and development targets lie in relatively shallow (less than 200m deep) water where the (sub-)seabed is characterized by corals and near-surface channels. This impacts the seismic image through the resulting variation of near-surface velocities as well as attenuation owing to scattering and negatively impacts the deeper structural imaging. An illustration of these challenges is shown in Figure 1. The subsurface offshore and onshore Brunei is also heavily faulted and large anticlines often have steep flanks, and suffer from crestal collapses. Drilling targets can be relatively narrow (few 100 m wide) fault blocks near the crestal collapses, which makes accurate fault imaging and positioning and thus an accurate seismic velocity model absolutely crucial for confident well placement. Figure 2 shows the importance of accurate imaging for well placement: The image from the final isotropic model indicates that the well trajectory is on the intended side of the fault, while the well results showed the trajectory had crossed the fault and needed to be sidetracked. The subsequently built tilted transverse isotropic (TTI) model reveals that the trajectory has indeed crossed the fault. This example stresses the importance of detailed and accurate anisotropic model building.
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Reflection salt proximity
Authors Yingpin Li, Ben Hewett and Yingping LiKnowledge of salt boundary locations at the salt flanks and base is critically important for updating velocity models, getting better sub-surface images, estimating a reservoir size, and minimizing drilling risks for exploration and development wells in and near the salt. We have developed a Reflection Salt Proximity method to delineate the salt-sediment boundary. This method utilizes the reflected P waves off the salt face to calculate the Salt Reflection Points by measuring arrival times, azimuths, and vertical angles of the reflected PP waves with a sediment velocity model. This approach is complementary to the salt proximity migration, sediment proximity, and conventional salt proximity methods. An example in the Gulf of Mexico is used to demonstrate the method and to present the calculated salt reflection points, which are consistent with those results obtained from the conventional salt proximity surveys.
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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)