Retaining geological realism in dynamic modelling: a channelized turbidite reservoir example from West Africa

Alpak, Faruk O.; Barton, Mark D.; Castiñeira, David

doi:10.1144/1354-079309-033

Cited by 23 publications

(7 citation statements)

References 44 publications

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“…For example, interference testing between well pairs might be used to determine the degree of communication between the wells and quantify the extents of mudstone drapes. In a production setting, the extent of mudstone drapes along surfaces is a variable that could be modified to get a history match between model predictions of reservoir performance and observed behavior (e.g., Stright, 2006, Alpak et al, 2011.…”

Section: Implications For Reservoir Performancementioning

confidence: 99%

Geologic and seismic modeling of a coarse-grained deep-water channel reservoir analog (Black’s Beach, La Jolla, California)

Stright¹,

Stewart²,

Campion³

et al. 2014

Bulletin

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Beach north of La Jolla, California, record a deep-water channelized slope system of an Eocene forearc basin. The outcrop exposure, which is approximately 100 m (330 ft) high by 1.7 km (~1 mi) long, offers insight into reservoir distribution and connectivity within coarse-grained, confined, deep-water channel systems. To use this outcrop as a quantitative subsurface analog, a detailed two-dimensional lithologic model was constructed from measured sections and interpreted photopanels. Elastic rock properties, including compressional-wave velocity, shear-wave velocity, and density typical of shallow offshore west African reservoirs were used to construct an impedance model. This model was convolved with 15-, 25-, and 50-Hz quadrature-phase Ricker wavelets to generate near-and far-angle stack one-dimensional and two-dimensional synthetic seismic reflection models. Because deep-water lithofacies have distinct amplitude-variation-withoffset behaviors and the interpretation of surfaces is intimately coupled with predicting lithofacies, simple bed interface models of conglomerate, sandstone, interbedded sandstone and mudstone, and muddy sandy debrite were used to build a template for successful interpretation.Interpretation of these forward seismic models demonstrates (1) the limits of and uncertainty associated with the interpretation of seismic data at different frequencies commonly encountered in the exploration, development, and production of deep-water reservoirs; and (2) how the combination of near-and far-angle seismic data can be used to interpret channel-fill lithofacies and Lisa Stright is an assistant professor of hydrocarbon geosciences in the Department of Geology and Geophysics at the University of Utah. She leverages her combined engineering and geology background to couple quantitative observations from outcrop analogs and subsurface data sets to build more predictive geocellular and flowsimulation models. She works specifically in siliciclastic reservoir characterization and modeling. is W. J. and M. L. Crook Professor and associate dean of Academic Affairs, School of Earth Sciences, Stanford University. His research foci include the tectonics of sedimentary basins, basin and petroleum systems modeling, and deep-water siliciclastic depositional systems. He is a recipient of AAPG's Sproule Award and Grover E. Murray Memorial Distinguished Educator Award.

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Section: Implications For Reservoir Performancementioning

confidence: 99%

Geologic and seismic modeling of a coarse-grained deep-water channel reservoir analog (Black’s Beach, La Jolla, California)

Stright¹,

Stewart²,

Campion³

et al. 2014

Bulletin

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“…This approach also overcomes one of the principal weaknesses of stochastic algorithms: slow convergence. An improved in-house implementation of NA is described in Alpak et al (2011) and used in the conventional (nonimproved) mode in this work.…”

Section: Stochastic Data-integration Methodsmentioning

confidence: 99%

“…The rock-physics model, resolution of the seismic detection, water-saturation changes triggering detection, and thickness of the water-invaded zones are not only based on the analysis of data from the reservoir of interest but also on the assimilation of data from analog reservoirs of the same field that have undergone water breakthough. On the other hand, the relative permeability effects are taken into account by means of the 3D connectivity method previously developed and applied for channelized turbidite reservoirs (Alpak et al 2010;Alpak et al 2011). The method is applied for the first time to the lobate turbidite stratigraphic architecture within the context of the study reported in this paper.…”

Section: Comparison Of the Pso And Vfsa Methods In A Field Casementioning

confidence: 99%

“…A rapid-running dynamic (forward) model is crucial within a history-matching framework, especially when the sampling is carried out by a stochastic engine (e.g., PSO, VFSA, and NA). The 3D connectivity method is enabler technology for rapid dynamic models that robustly account for the multiphase-flow effects of subgrid-scale stratigraphic-reservoir elements (Alpak et al 2010;Alpak et al 2011). …”

Section: Comparison Of the Pso And Vfsa Methods In A Field Casementioning

confidence: 99%

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A Comparison of Stochastic Data-Integration Algorithms for the Joint History Matching of Production and Time-Lapse-Seismic Data

Jin

Hoek

Alpak

et al. 2012

SPE Reservoir Evaluation &Amp; Engineering

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Quantitative integration of spatial and temporal information provided by time-lapse (4D) -seismic surveys to dynamic reservoir models calls for efficient and effective data-integration algorithms. We carry out a comprehensive comparison of stochastic optimization methods using both a synthetic and a field case.Our first case is a challenging synthetic test problem known as the Imperial College Fault Model (ICFM). The methods of veryfast simulated annealing (VFSA), particle-swarm optimization (PSO), and the neighborhood algorithm (NA) are compared in terms of convergence characteristics, data-match quality, and posterior model-parameter distributions. On the basis of the knowledge developed from the ICFM problem, we isolate VFSA and PSO and evaluate their performance further on a field case involving a deepwater reservoir undergoing waterflooding. The field case has a reasonably long production history and good-quality 3D-and 4D-seismic data, allowing the construction of a geologically consistent model by means of dynamic calibration. As such, it constitutes a relevant field test for joint seismic/production history matching. We assess the data-match characteristics and the quality of dynamic forecasts delivered by VFSA and PSO in the field case.Practical guidelines are developed over the course of these studies for selecting a "fit-for-purpose" optimal method for joint history-matching workflows. Our results show that PSO, a population-based method, incurs relatively more computational expense at a given iteration but exhibits good convergence characteristics and provides multiple history-matched models. The PSO method has emerged as more effective compared with the NA and VFSA methods in the ICFM problem. It was also quite effective on the field application. On the other hand, the VFSA method requires comparatively more iterations to converge because of its sequential nature, but it has advantageous features when moderate computing resources are available.

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“…Flow-relevant stratigraphic examples of such multiscale architectures occur in clastic reservoirs, for example, in turbidite channels (Alpak et al 2010(Alpak et al , 2011(Alpak et al , 2013, in turbidite lobes, and in clastic shallow marine and fluvial deposits (Alpak and van der Vlugt 2014). Flow-relevant stratigraphic examples of such multiscale architectures occur in clastic reservoirs, for example, in turbidite channels (Alpak et al 2010(Alpak et al , 2011(Alpak et al , 2013, in turbidite lobes, and in clastic shallow marine and fluvial deposits (Alpak and van der Vlugt 2014).…”

Section: Introductionmentioning

confidence: 99%

Quasiglobal Multiphase Upscaling of Reservoir Models With Nonlocal Stratigraphic Heterogeneities

Alpak

2014

SPE Journal

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Representing the complete spectrum of fine-scale stratigraphic details in full-field dynamic models of geologically complex clastic reservoirs is beyond the limits of existing computational capabilities. A quasiglobal multiphase upscaling method-the regional-scale multiphase upscaling (RMU) method-is developed, in which the dynamic effects of subgrid-scale (typically subseismic) nonlocal stratigraphic reservoir elements (e.g., channels, lobes, sand bars, and shale drapes) are captured by means of pseudofunctions for flow simulation. Unlike conventional dynamic multiphase upscaling methods, the RMU method does not require fine-resolution reservoir-scale simulations. Rather, it relies on intermediate-scale sectormodel simulations for pseudoization. The intermediate scale, also referred to as the regional scale, is defined as the spatial scale at which the global multiphase flow effects of nonlocal stratigraphic elements can be approximated by fine-resolution flow simulations with reasonable accuracy. During the pseudoization process, dynamic multiphase flow responses of coarse regional-scale sector models are calibrated against those stemming from their corresponding fine-resolution parent models. Each regional-scale sector model is simulated only once at the fine geologic resolution. The process involves automatic determination and subsequent modification of the parameters that describe rock relative permeability and capillary pressure functions. Coarse regional-scale models are simulated a few times until a reasonable match between their coarse-and fine-resolution dynamic responses can be attained. The parameter-estimation step of the pseudoization process is performed by use of a very efficient constrained nonlinear optimization algorithm.The RMU method is evaluated in two proof-of-concept numerical examples involving a plethora of turbidite stratigraphic architectures. The method yields simulation results that are always more accurate than conventionally upscaled coarse-resolution model predictions. Incorporating geologically based pseudofunctions into otherwise simple coarse-resolution full-field reservoir models reduces the simulation cycle time significantly and improves the accuracy of production forecasts. The RMU method typically delivers two to three orders of magnitude in speed up of flow simulations.

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Retaining geological realism in dynamic modelling: a channelized turbidite reservoir example from West Africa

Cited by 23 publications

References 44 publications

Geologic and seismic modeling of a coarse-grained deep-water channel reservoir analog (Black’s Beach, La Jolla, California)

Geologic and seismic modeling of a coarse-grained deep-water channel reservoir analog (Black’s Beach, La Jolla, California)

A Comparison of Stochastic Data-Integration Algorithms for the Joint History Matching of Production and Time-Lapse-Seismic Data

Quasiglobal Multiphase Upscaling of Reservoir Models With Nonlocal Stratigraphic Heterogeneities

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