Study of key parameters of reservoir viz, porosity, water saturation, permeability and pore size distribution from well logging data is more complicated in carbonate reservoir due to geological heterogeneities than Clastic reservoir.The Magnolia field is located in GOM blocks GB 783 and 784 and produces from Plio-Pleistocene turbiditic sands that form a complex channel/levee sequence penetrated by 16 boreholes. The primary pays consist of two sands, each about 200 feet thick, separated by a 15 foot shale layer. The pays are divided into an eastern gas prone province and a western oil prone province. A reservoir flow simulation model is planned to optimize production from existing wells and to facilitate future field development. Construction of an accurate model is complicated by MDT pressure measurements which indicated compartmentalization below the resolution of conventional seismic analysis, and by overlap of the seismic attributes derived from producing reservoirs, wet sands, and shales.To mitigate these factors, geostatistical inversion was chosen to produce the rock property inputs for the flow simulation models. This approach allowed development of a rock properties model consistent with core data, log data, and geologic constraints as well as seismic information. It also allowed assessment of uncertainty through the generation of a statistically significant number of internally consistent alternate solutions (realizations). A Markov Chain Monte Carlo method was employed to integrate borehole and geologic information to produce acoustic impedance and lithology volumes which were then used to co-simulate porosity, permeability, p-wave velocity, and water saturation volumes. Multiple realizations of these products were reviewed, uncertainty was assessed, and a rock properties model was selected for conversion to a flow simulation modeling format. The entire process can be rerun relatively quickly to accommodate additional wells and improved seismic data or to match production history.
The Tempest 3D model and dataset were generated to test industry's ability to correctly image deep water Gulf of Mexico subsalt structures. The project included four steps: (a) design of a 3-dimensional model based on real Gulf of Mexico geology; (b) acquisition design that included narrow azimuth, mid (range) azimuth and wide azimuth geometries; (c) numerical simulation using twoway wave equation algorithm and construction of three synthetic datasets; (d) application of various prestack depth migration algorithms for testing of subsalt imaging quality. The project parameters acquisition design and prestack depth migration algorithm parameters were all selected based on a single guideline: to be done as close as possible to field data acquisition and imaging. By following this guideline we obtained a dataset which realistically represents our ability to resolve subsalt imaging challenges. In this paper we present the project steps and demonstrate its main results.
Performing accurate depth-imaging is an essential part of deep-water Gulf of Mexico exploration and development. Over the years, depth-imaging technology has provided reliable seismic images below complicated salt bodies, and has been implemented in workflows for both prospect generation as well as reservoir development. These workflows include time domain preprocessing using various multiple elimination techniques, anisotropic model building, and depth-imaging using anisotropic reverse time migration (RTM). However, the accuracy of the depth-migrated volumes is basically unknown because they are tested only in the locations where a well is drilled. In order to learn about the accuracy of anisotropic deep water Gulf of Mexico model building, and depth-imaging tools which are used for processing and imaging of field acquired data, we created a 3D vertical transverse isotropic (VTI) anisotropic earth model and a 3D seismic data set representing subsalt Gulf of Mexico geology. The model and data set are referred to as the Tempest data set, the original being created several years ago. The recent model and data set were created incorporating upgraded technology to reflect recent developments in data acquisition, model building and depth-imaging. Our paper presents the new Tempest anisotropic model, data set, and RTM prestack depth-migration (PSDM) results. The Tempest RTM PSDM is being used to learn about the differences between the exact geological model and the RTM PSDM image, helping in the interpretation of real RTM prestack depthmigrated data.
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