A reservoir characterization study in the Burgos Basin including simultaneous prestack inversion and lithology prediction

Garcia, Gorka; Sanz, Carlos; Sherratt, Peter; Assefa, S.; Pallottini, Fabio; Bendel, Eduardo; y, Jose Luis Arroyo; Rosa, Victor Hugo de la

doi:10.1190/1.3255201

Cited by 2 publications

(2 citation statements)

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“…More advanced forms of seismic data inversion (pre‐stack) may be used to discriminate lithology from seismic data using classification techniques. The resulting seismic litho classes are then used to condition the inter‐well space through co‐kriging or co‐simulation with well logs . Methods for leveraging acoustic and elastic seismic inversion products, originally developed for oilfield applications, have been applied in various CO 2 projects.…”

Section: Geologic Modelmentioning

confidence: 99%

“…This is used in combination with the neutron and sonic for lithology identifi cation as well as identifi cation of fl uids in the porosity; HTNP space through co-kriging or co-simulation with well logs. 5 Methods for leveraging acoustic and elastic seismic inversion products, originally developed for oilfi eld applications, have been applied in various CO 2 projects. Researchers developing a model for a carbonate formation candidate for saline CO 2 sequestration in Kansas investigated both pre-stack and post-stack seismic inversion methods for conditioning of porosity interpolation for reservoir simulation models.…”

Section: Petrophysics and Geologymentioning

confidence: 99%

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Integrated reservoir modeling at the Illinois Basin – Decatur Project

2014

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Injecting carbon dioxide (CO2) into the subsurface comes with the added responsibility of understanding the movement of the CO2 once injected, and ensuring that it remains contained in the target reservoir. Consequently, a significant part of the sequestration process is to build and maintain models of the subsurface that will predict the flow of the injected CO2. These models need to integrate all data available so that the subsurface movement of the CO2 can be predicted should changes to the injection parameters be made. As the CO2 plume is monitored by various measurements, the model needs to be flexible enough to be updated to account for any difference between predicted and known behavior. An integrated predictive reservoir model was created for the Illinois Basin – Decatur Project utilizing a variety of data collected from 2007 until January 2013. The evolution of this model will be discussed. Prior to the beginning of injection, in November 2011, reservoir models and numerical simulations were used extensively to design the wellbore, completions, and well tests; optimize predicted injectivity; simulate the CO2 subsurface migration development and pressure perturbation; analyze and understand well test results; and quantify uncertainties in predictions. Now, with the help of dynamic injection data collected, the calibration of the model has been accomplished by honoring the observations and this facilitates making more informed forecasts. Our analysis indicates a laterally developing CO2 subsurface migration, thus reducing the near to mid‐term expectation of CO2 reaching the seal and upper sections of target reservoir. Further planned modeling efforts include additional model refinements required for anticipated future applications including regulatory compliance and multi‐physics data integration.

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Section: Geologic Modelmentioning

confidence: 99%

Section: Petrophysics and Geologymentioning

confidence: 99%