Case Study 1
Mangara Field, Doba Basin - Chad, North Africa
The reservoir units consist of interbedded sands and shales of different thicknesses. The resulting variability in properties requires accurate characterization for field development.
Extensive rock-physics modelling was used to create crossplot templates of different net-to-gross and porosity scenarios. This provided the detailed plan for the interpretation of the inversion attributes. The inversion itself incorporated a number of advanced components, including a heavily faulted initial model, VSP data to assist with well placement, and depth conversion of the final results guided by the processing velocities, but matched to well depths. Assistance was also provided for ensuring the AVO compatibility during the seismic data processing.
Case Study 2
Horn River Basin, Northeast B.C., Canada
Predict geologic properties of a shale reservoir interval to guide production and completion planning for successful development of the reservoir. Determining reservoir and mechanical properties of the shale units is important for successful placement of horizontal wells for efficient multi-stage hydraulic fracturing and maximum gas production.
Quantitative analysis of prestack multicomponent data in this study, combined with detailed well analysis in crossplots, reveals detailed distinctions between reservoir units and relative measures of porosity and brittleness properties within each unit. Using key elastic properties derived from the seismic data analysis calibrated by well data templates, lithological units were classified, and then, in turn, subclassified based on unit-specific reservoir properties.
Case Study 3
McMurray Formation, Athabasca Oil Sands, Alberta, Canada
Predict lithology variations and fluid types within the reservoir. Accurate placement of horizontal wells for steam injection and oil production requires confident estimates of oil/water contacts and reservoir properties.
Comprehensive analysis of well data, including dipole sonic logs for shear velocity gave the confidence necessary to use elastic properties derived from detailed quantitative analysis of prestack multicomponent data. Bitumen-saturated sand, water-saturated sand, shale, mixed facies, and cemented sand predictions were all determined, and the high-resolution results were validated with blind wells.