BP Seismic Inversion Technology Commercialized by Cegal

BP’s unique One Dimensional Stochastic Inversion (ODiSI) method has been turned into a commercial application by Cegal, ready to be used by the industry in Petrel.

BP’s unique One Dimensional Stochastic Inversion (ODiSI) method has been turned into a commercial application by Cegal, ready to be used by the industry in Petrel E&P software platform.
Being one of the big companies at the forefront of oil and gas technology, we often hear about innovations going on at BP. From them building the largest commercially used supercomputer, to their innovative algorithms for deep-water exploration, they are pushing the capabilities of modern technology to their limits.

Inverting seismic traces to derive geological parameters is a fundamental goal for the geophysicist, by which there are many techniques available.

ODiSI is a new method that produces high-quality reservoir property estimates with associated uncertainties. Unlike many other inversion methods, BP’s unique method specifically includes only the most robust prior information, in order to apply additional constraints to the solution.

ODiSI: Fit for Purpose

ODiSI is a joint facies inversion estimation process, which estimates reservoir properties and impedances together, and all their associated uncertainties. It does this by matching the seismic to a very large number of pseudo-wells simultaneously to multiple angle-stacks.

Inversion is usually applied to seismic data in the late appraisal stage and onwards; by this time, you tend to have a lot of knowledge about your reservoir. Typically, you would have a pretty good understanding of your depositional environment and the stratigraphy; you will have some well-logs providing rock property relationships, some depth trends, and vertical statistics that you can measure. In addition, you would probably have some information about the fluid contacts.

For any inversion project, you would ideally want to make use of all this information and integrate it all within the inversion. The real challenge is how you bring together such a dissimilar quantity of information, within one inversion package. 

The way ODiSI does this is by generating pseudo-wells, which are fully consistent with all your prior knowledge. Each pseudo-well comprises a full suite of petrophysical curves; in other words, it is really much like a real well. Hence, it is called pseudo-wells.

The pseudo-wells are each calibrated to real-world data, where a sophisticated model for the vertical statistics is applied, and a rock physics model is used to build up the full suite of curves. The range of properties in the pseudo-wells is constrained by your prior expectations of the reservoir. 

The quality of the results is very much dependent on the quality of the pseudo-wells, so a lot of effort is put into making these pseudo-wells geologically as realistic as possible.

Supporting the Industry

BP decided to commercialize the ODISI algorithm in late 2014 and invited software companies to partake in a competitive tender process. One of BP’s conditions was to integrate the algorithm, initially developed in MATLAB, into Petrel*, the leading software used for exploration and in modeling reservoirs. 

Many well-known software vendors in the field fought for the win. Having domain expertise in reservoir characterization and inversion, Cegal, also the market leader in Ocean development for Petrel stood out from the crowd.

BP awarded Cegal the contract in January 2015, and the project progressed rapidly.

Read also: One Dimensional Stochastic Inversion (ODiSI) Success Stories

Commercializing the Algorithm

The development of the project itself was a sprint process which ran from May 2015 through to September the same year. Cegal worked closely with BP throughout, delivering weekly installers for testing and feedback, and held weekly review meetings.

“Cegal has done a tremendous job re-engineering BP’s internal code into an accessible, transparent and fully integrated product for the Petrel environment”, Pat Connolly of PCA Ltd said in a press release.

In 2016 the project was licensed as Blueback ODiSI and deployed globally by BP and used by inversion teams on different fields and inversion challenges across the world. 

“ODiSI has already been used successfully in a variety of siliciclastic fields. The output volumes of net-to-gross and porosity are being used by the field teams for well planning, for enhancing the geological understanding of the reservoir interval, and as direct inputs to the reservoir model”, according to BP geophysicist Sarah Grant.

Read also: Effective Seismic Inversion Through Microsoft Azure Cloud

Cegal’s Inversion Services

Cegal has a wealth of experience in running ODISI service projects for a variety of clients globally. Clients deliver the required partial angle stack volumes and well-log inputs for Cegal to evaluate and optimize the chi angle projections and colored inversion parameters to create the required inputs for ODiSI. Once the inversion is executed, all ODiSI products are delivered back to the client.

Blueback ODiSI Plugin for Petrel

The Blueback ODiSI is available as an OCEAN plugin for the Petrel platform and is also a part of, and complement to, Cegal’s Quantitative Interpretation solution, Blueback Rocks QI

Cegal has been collaborating closely with BP over the last couple of years to develop the technology further as it continues to mature and is excited to publish Blueback ODiSI version 3.0 in 2019.

Click to Download Case study: Central North Sea, Upper Jurassic Fulmar Inversion utilizing ODiSi One Dimensional Stochastic Inversion

*Petrel is a mark of Schlumberger. 

See also: Blueback ODiSI

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Mark O'Brien

Written by Mark O'Brien

Mark O’Brien has over 18 years industry experience within the E&P industry.  He has held a variety of positions working for both operators and service companies on and offshore as a reservoir geologist, geomodeler, GIS consultant and technical sales consultant.

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Central North Sea, Upper Jurassic Fulmar Inversion utilizing ODiSi One Dimensional Stochastic Inversion

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