Advanced Resources and Risk Technology LLC

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Advanced Resources and Risk Technology LLC

Sunnyvale, CA, United States
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Stright L.,University of Utah | Bernhardt A.,University of Potsdam | Boucher A.,Advanced Resources and Risk Technology LLC
Mathematical Geosciences | Year: 2013

Facies bodies in geostatistical models of deep-water depositional environments generally represent channel-levee-overbank-lobe morphologies. Such models adequately capture one set of the erosional and depositional processes resulting from turbidity currents traveling downslope to the ocean basin floor. However, depositional morphologies diverge from the straight forward channel-levee-overbank-lobe paradigm when the topography of the slope or the shape of the basin impacts the timing and magnitude of turbidity current deposition. Subaqueous mass-transport-deposits (MTDs) present the need for an exception to the channel-levee-overbank-lobe archetype. Irregular surface topography of subaqueous MTDs can play a primary role in controlling sand deposition from turbidity currents. MTD topography creates mini-basins in which sand accumulates in irregularly-shaped deposits. These accumulations are difficult to laterally correlate using well-log data due to their variable and unpredictable shape and size. Prediction is further complicated because sandstone bodies typical of this setting are difficult to resolve in seismic-reflection data. An event-based model is presented, called DFTopoSim, which simulates debris flows and turbidity currents. The accommodation space on top of and between debris flow lobes is filled in by sand from turbidity currents. When applied to a subsurface case in the Molasse Basin of Upper Austria, DFTopoSim predicts sand packages consistent with observations from core, well, and seismic data and the interpretation of the sedimentologic processes. DFTopoSim expands the set of available geostatistical deep-water depositional models beyond the standard channel-levee-overbank-lobe model. © 2013 International Association for Mathematical Geosciences.

Wilson C.E.,Stanford University | Wilson C.E.,Chevron | Aydin A.,Stanford University | Aydin A.,Ford Motor Company | And 4 more authors.
AAPG Bulletin | Year: 2011

We undertake a multidisciplinary investigation into the distribution of asphalt in the Anacacho Limestone in an effort to decipher the potential roles of fractures and faults on secondary hydrocarbon migration. Field relationships between fractures, faults, and asphalt are evaluated at an asphaltic limestone mine near Uvalde, Texas. Based on their distributions, geometries, and structural relationships, we infer that normal faults provided vertical flow paths through the Anacacho Limestone, whereas strata-bound fractures enhanced lateral permeability. Variograms calculated from 75 subsurface measurements indicate that the asphalt concentration is anisotropically correlated and that the longest correlation length points in the mean strike direction of fractures and faults. A globally positioned laser rangefinder is used to measure faults and stratigraphic contacts within the mine. That data are then combined with lithologic descriptions from surrounding subsurface wells to construct a three-dimensional (3-D) model of the Anacacho Limestone. When an ordinary block-kriging algorithm populates the model with asphalt concentration estimates, the high values align along a trend that connects the two largest normal fault zones at the mine. The 3-D model provides a framework to numerically simulate secondary hydrocarbon migration. We test numerous hydrocarbon migration scenarios by adjusting simulation parameters within physically realistic ranges until producing an oil saturation field that agrees with asphalt concentration estimates. Our best match simulation indicates that oil entered the Anacacho Limestone through normal faults, that regional aquifer flow impacted oil flow, and that fractures increased the horizontal permeability of the formation by an order of magnitude along their strike direction. Copyright ©2011. The American Association of Petroleum Geologists. All rights reserved.

Horgue P.,CNRS Fluid Dynamics Institute of Toulouse | Guibert R.,CNRS Fluid Dynamics Institute of Toulouse | Gross H.,Advanced Resources and Risk Technology LLC | Creux P.,CNRS Laboratory of Thermodynamics and Energetics of Complex Fluids | Debenest G.,CNRS Fluid Dynamics Institute of Toulouse
Computational Geosciences | Year: 2015

This work presents a new subdivision method to upscale absolute permeability fields. This process, called two-step method, consists in (i) solving micro-scale equations on subdomains obtained from the full domain regular decomposition and (ii) solve a second upscaling with Darcy’s law on the permeability fields obtained in the first step. The micro-scale equations used depend on the case studied. The two-step upscaling process is validated on randomly generated Darcy-scale permeability fields by measuring the numerical error induced by upscaling. The method is then applied to real domains obtained from sandstone micro-tomographic images. The method specificities due to pore-space structure are discussed. The main advantage of the two-step upscaling method resides in the drastic reduction of computational costs (CPU time and memory usage) while maintaining a numerical error similar to that of other upscaling procedures. This new upscaling method may improve permeability predictions by the use of finer meshes or larger sample volumes. © 2015, Springer International Publishing Switzerland.

Boucher A.,Advanced Resources and Risk Technology LLC | Costa J.F.,Federal University of Rio Grande do Sul | Rasera L.G.,Federal University of Rio Grande do Sul | Motta E.,Federal University of Rio Grande do Sul
Mathematical Geosciences | Year: 2014

Applications of multiple-point statistics (mps) algorithms to large non-repetitive geological objects such as those found in mining deposits are difficult because most mps algorithms rely on pattern repetition for simulation. In many cases, an interpreted geological model built from a computer-aided design system is readily available but suffers as a training image due to the lack of patterns repetitiveness. Porphyry copper deposits and iron ore formations are good examples of such mining deposits with non-repetitive patterns. This paper presents an algorithm called contactsim that focuses on reproducing the patterns of the contacts between geological types. The algorithm learns the shapes of the lithotype contacts as interpreted by the geologist, and simulates their patterns at a later stage. Defining a zone of uncertainty around the lithological contact is a critical step in contactsim, because it defines both the zones where the simulation is performed and where the algorithm should focus to learn the transitional patterns between lithotypes. A larger zone of uncertainty results in greater variation between realizations. The definition of the uncertainty zone must take into consideration the geological understanding of the deposit, and the reliability of the contact zones. The contactsim algorithm is demonstrated on an iron ore formation. © 2013 International Association for Mathematical Geosciences.

Boucher A.,Advanced Resources and Risk Technology LLC | Dimitrakopoulos R.,McGill University
Mathematical Geosciences | Year: 2012

Mineral deposits frequently contain several elements of interest that are spatially correlated and require the use of joint geostatistical simulation techniques in order to generate models preserving their spatial relationships. Although joint-simulation methods have long been available, they are impractical when it comes to more than three variables and mid to large size deposits. This paper presents the application of block-support simulation of a multi-element mineral deposit using minimum/maximum autocorrelation factors to facilitate the computationally efficient joint simulation of large, multivariable deposits. The algorithm utilized, termed dbmafsim, transforms point-scale spatial attributes of a mineral deposit into uncorrelated service variables leading to the generation of simulated realizations of block-scale models of the attributes of interest of a deposit. The dbmafsim algorithm is utilized at the Yandi iron ore deposit in Western Australia to simulate five cross-correlated elements, namely Fe, SiO 2, Al 2O 3, P and LOI, that are all critical in defining the quality of iron ore being produced. The block-scale simulations reproduce the direct- and cross-variograms of the elements even though only the direct variograms of the service variables have to be modeled. The application shows the efficiency, excellent performance and practical contribution of the dbmafsim algorithm in simulating large multi-element deposits. © 2012 International Association for Mathematical Geosciences.

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