3D Reservoir Visualization

Bui-Tran, Van; Pajon, Jean-Louis; Phillipe, Joseph; Chautru, Jean-Marc

doi:10.2118/22301-pa

Cited by 6 publications

(1 citation statement)

References 4 publications

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“…With the emergence of the first 3D visualization technologies for oil & gas in the early 90's, like in the work of [1], proponents were striving to provide fundamental understanding on reservoirs, powered by dedicated SGI workstations. Later, PCs had grown powerful enough to enable local graphics processing, thus contributing to a widespread usage of visualization in nearly every discipline in E&P. However, with the exponential growth in computational capacity, there was also an exponential growth in the size, resolution and complexity of the data to be handled.…”

Section: Introductionmentioning

confidence: 99%

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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Section: Introductionmentioning

confidence: 99%