Advanced Visualization for Reservoir Simulation

Al-Harbi, Badr Mohammed; Al-Darrab, Abdulaziz; Al-Zawawi, Ahmed S.; Al-Zamil, Khalid

doi:10.2118/168103-ms

Cited by 5 publications

References 14 publications

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Integrated geologic, geophysical, and petrophysical data to construct full field geologic model of Cambrian-Ordovician and Upper Cretaceous reservoir formations, Central Western Sirte Basin, Libya

et al. 2019

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The Cambrian-Ordovician and Upper Cretaceous formations, which are the main oil-producing formations in the central Sirte Basin, are structurally complex. The lateral and vertical heterogeneity of the reservoir formations is not well-understood, which negatively affects the performance of the reservoirs. We constructed efficient full-field static models that incorporate the lateral and vertical variation of those reservoir formations by integrating geologic and geophysical data. We determined lithology and reservoir properties by selecting appropriate petrophysical techniques that suit the available well data and overcome issues with unreliable well-log measurements. In the process of building structural models, defining and mapping the base of the Cambrian-Ordovician Gargaf Formation was very challenging because wells did not penetrate the basal formation, and the quality of the seismic data decreases with depth. Therefore, we applied techniques of adding isochore maps of the overlying Upper Cretaceous of the Bahi and Waha Formations to map basal contact and determine the thickness of the Gargaf Formation for the first time in the area. The constructed isochore maps showed the thickness variation and the distributions of the Bahi and Waha Formations and explained the influence of Gargaf paleotopography and faults on them. The fault models combined with facies and property models suggested an interconnection among the three main reservoirs. They also indicated that the quality of the Waha reservoir enhances as the lithology varies from limestones to calcareous sandstones, whereas the quality of the Gargaf reservoir was primarily controlled by fractures. The total estimate of the original oil in place with the largest contribution of hydrocarbon volume from the Waha Formation was [Formula: see text] stock tank barrel. The created model with a fine-scale geocellular covering an area of [Formula: see text] is unique to the study area and it can be updated and refined at any time with new data production and drilling activities.

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Integrated geologic, geophysical, and petrophysical data to construct full field geologic model of Cambrian-Ordovician and Upper Cretaceous reservoir formations, Central Western Sirte Basin, Libya

et al. 2019

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Enhancing Reservoir Understanding by Utilizing Business Intelligence Workflows

et al. 2013

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Saudi Aramco Upstream data volumes have been exploding exponentially over the past few years. Reservoir engineers need to quickly analyze huge volumes of multidisciplinary data coming from multiple sources scattered across the upstream business, such as simulation, seismic, corporate database and real time data from intelligent fields. In addition, it is crucial to capture the scattered multidisciplinary experience that Saudi Aramco has across the upstream business. Multidisciplinary professionals are utilizing many expert systems that require specialized experience in their areas. It is very important to break these silos and bridge the gaps to capture all the scattered knowledge and experience in an integrated media to build shared understanding within multidisciplinary teams. Business intelligence provides a platform for guided processes and workflows that help to overcome these challenges. The developed reservoir engineering business intelligence workflows will help engineers to analyze, visualize and report reservoir simulation results, production development scenarios and economics to enhance decision making process. This paper will discuss the Saudi Aramco methodology to develop reservoir engineering business intelligence workflows that utilize advanced data mining, visual analytics, and predictive analytics techniques. In addition, we will review several workflows that improve the process of history matching and prediction by rapidly identifying trends, anomalies, outliers and patterns in the reservoir simulation results.

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Cloud-based Remote Visualization of Big Data to Subsurface Exploration

Binotto¹,

Sultanum²,

Cerqueira³

2014

All Days

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Since the first visualization solutions were explored for O&G, major technical improvements enabled gigabyte-sized models to be rendered and manipulated at interactive speeds. Yet, other fundamental aspects such as data access and distribution are often overlooked in the process, even to date. Data movement may often be prohibitive, either due to legal constraints (data is restricted from departing the country) or practical considerations (data is too large to be moved, is a checkpoint tightly connect to imaging processes, and requires costly resources to be manipulated). Collaborative visualization tends to be performed co-locally, following an explicit, manually conducted, data transfer to a dedicated visualization machine.We propose an alternative based upon data-centric computing. The model offers visualization as-a-service over a multi-tenant cloud-based environment. Remote visualization enables lightweight access and interaction with generated data readily after the processing, dismissing the need to transfer the whole dataset into analyst's machine. It offloads heavy graphics processing to a cloud server featuring the necessary infrastructure to handle such voluminous data, like GPUs, GPFS, and ultimately sends only a reduced output to lightweight clients (rendered images/geometry). Visualization resources can also be shared among concurrent users in a web-based interface and combined with other data sources, like correspondent well information or velocity models, facilitating effective remote collaboration towards knowledge discovery in subsurface exploration. Ubiquitous on-the-go data access (e.g., in the exploration field itself) is thereby made possible through mobile interfaces.Concurrently, several challenges emerge with the aforementioned visualization model. The effective resource distribution of different data sources among several clients needs to benefit from the cloud execution platform. The OpenPower Foundation is an example of the future HPC platform that can be customized to O&G characteristics and be offered as a cloud model.

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Advanced Visualization for Reservoir Simulation

Cited by 5 publications

References 14 publications

Integrated geologic, geophysical, and petrophysical data to construct full field geologic model of Cambrian-Ordovician and Upper Cretaceous reservoir formations, Central Western Sirte Basin, Libya

Integrated geologic, geophysical, and petrophysical data to construct full field geologic model of Cambrian-Ordovician and Upper Cretaceous reservoir formations, Central Western Sirte Basin, Libya

Enhancing Reservoir Understanding by Utilizing Business Intelligence Workflows

Cloud-based Remote Visualization of Big Data to Subsurface Exploration

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