White Papers
One of the most critical elements in well and field evaluation is minimizing uncertainty. The standard practice is to perform both petrophysics and rock physics, but this is insufficient if done in a linear fashion. The best practice is to tightly integrate rock physics with petrophysics such that processes, parameters and models are as consistent as possible. This yields a much more reliable analysis, but the practicality of this approach depends on the tools used in the analysis.
Uncertainty will always play a dominant role in oil field exploration and development. Because uncertainty drives costs, quantifying and minimizing that uncertainty is a primary goal for asset teams. To achieve this goal, geologists and geoscientists must make sense of disparate data, bringing together a myriad of information from different sources and with varying measurement scales. To further complicate the analysis, the data are always sparse and incomplete, leaving vast areas of the subsurface unmeasured.
Rising to this challenge is a new best practice: combining well, seismic and other data through 3D Geostatistical Inversion. Validated by leading industry experts, this best practice has proven its value in producing highly-detailed, realistic 3D numerical reservoir models with more accurate estimates of uncertainty and less bias than other reservoir modeling and characterization methods.
A new approach now makes modeling and simulation a practical component of ongoing field management. It creates a highly detailed model that easily incorporates new operational data and can be updated anywhere in the workflow, from seismic to simulation. Its iterative workflow approach takes significantly less time, allowing operators to keep up with drilling schedules. Real-world use has shown a 3-5x speed up in modeling and maintenance tasks.
Most oil and gas exploration and production companies have a substantial investment in seismic data and interpretation of that data. This data contains a wealth of information about the reservoir properties between the well locations, and this information would be of great interest to geologic modelers if only it were available in a form they could make use of in their geologic models.
|
