Improved, flexible and faster access to critical data is vital for fully informed decision making in today’s multidisciplinary asset development teams. It is also imperative to include the highest fidelity quantitative temporal data when building reservoir models to improve development plans and maximize returns on investment.
Fracture Propagation Analysis from Inter-well Tracer and Microseismic Data
Following an inter-well tracer study for their field, an onshore group was given the results of the study in the format of spreadsheets and 2D charts. The spreadsheet data were particularly difficult to interpret and the group felt a 3D/4D visualization of the tracer results was critical to fully understand them. Furthermore, the group wanted to integrate the tracer data with other field data that could potentially help with the tracer interpretation, including offset well trajectories, well logs, property models, microseismic data and horizon surfaces.
A Relief Well Planning Case Study
In the Gulf of Mexico, a drilling trajectory needed adjusting due to a recent update to the reservoir model. Although the change to the trajectory was minor, the shift of the placement of the 14-inch and 11 7/8-inch casing shoes invalidated the previously designed relief well plans. With a fast-approaching deadline for drilling operations, the well planning team had little time to make a new relief well plan that could (1) achieve the objectives of the updated target plan, (2) meet industry-standard relief-well design constraints, and (3) be ready to send for permitting.
Monitoring CO2 Injection Volumes in the Subsurface—The Sleipner Field
Subsurface CO2 injection and storage is a proven technology for keeping carbon dioxide out of the atmosphere and ...
Advanced 3D Well Planning for Improved Wellbore Collision Avoidance
Planning a trajectory can be challenging in an open field, but when a drilling facility has dozens of existing ...
Well Location Optimization with Visual and Quantitative Analysis
An onshore team was tasked with producing a list of potential well landing locations based on attributes in a geological model. Four pad locations in the field were each given a set of 12 wells arranged in a radial pattern; the model’s potential target area covered a Z range of about 1650 ft. The well landing locations needed to be optimized to hit the model’s high Net to Gross (NTG) and Gamma Ray (GRD) areas because these two attributes had high confidence amongst the team. Finally, the potential well path landing options had to be easily visually ranked.
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