Coupled Flow Simulation in a Deepwater Reservoir: Fault Leakage Analysis
Bibliographic record
Abstract
Abstract Proper modeling of water injection projects in undeveloped deepwater reservoirs is important not only from a recovery factor point of view, but also for environmental protection purposes. Around the world some wells producing from reservoirs under water injection were shut down because of oil leakage to sea. Oil reservoirs with major faults that communicate the reservoir to the seabed are sensitive to water injection projects. Oil companies' common practice is to reuse the produced water and to reinject it into the reservoir. This procedure may cause pressure increase, and also may result in fault slip and communication through the fault from the reservoir to the seabed. Therefore, the flow simulation must consider concepts of shear and effective normal stress to estimate the maximum allowed pressure that generate slip in the fault, and, consequently, leakage to the seafloor. The main objective of this study is to explore the production uncertainties in an undeveloped oil reservoir, under water injection project, with a major internal fault, and the role of geomechanics in the fault reactivation. This study developed a new external iterative computational program applied to complex geological geometry that updates geomechanical information for each cell grid, for each time-step and during each Newton's iteration, to estimate the maximum pressure allowed to safely operate a water injection project without any oil leakage to the sea. This new methodology links two commercial simulators: one that emphasizes flow through porous media aspects, and the other that focuses on the geomechanical behavior. The investigations used triaxial laboratory tests performed in Brazil as support information. Sensitivity analyses of reservoir temperature, injection pressure and well location on the fault were carried out, and a comprehensive stress map and oil leakage variation, associated with flow through the fault, was also obtained. Introduction Exploitation of offshore deepwater reservoirs is a challenge to petroleum companies because of high direct development costs. Project costs may increase tremendously if wells need to be shut in or abandoned. A scenario where well this possibility exists occurs in a reservoir with a major fault that connects the petroleum field to the seafloor. During water injection operations the fluid pressure within the fault may increase to a value that leads to fault slip and hydrocarbon flow through the seabed. The hydrocarbon leakage can result in severe environmental damage and must be avoided. A proper simulation model that enables the evaluation of the maximum injection pressure allowed to impede oil leakage during water injection projects is a necessity. Once a reservoir has been discovered, it is essential to characterize it, as accurately as possible, to determine the most effective way of producing the recoverable oil. Reservoir characterization involves a great amount of data that includes the following: geology, laboratory and production data. Increasingly, geomechanical behavior of the reservoir has become an important aspect of the characterization workflow.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".