High Resolution, Real-Time Casing Strain Imaging for Reservoir and Well Integrity Monitoring: Demonstration of Monitoring Capability in a Field Installation
Bibliographic record
Abstract
Abstract Casing deformation can be used as a direct indicator or measurement of reservoir geomechanical strain, such as may occur with Vertical compaction accompanying pressure depletion of high-compressibility hydrocarbon reservoirs; Vertical strain dilation due to stress arching; Shear events associated with fault movement and reservoir bed boundary movement during subsidence; Localized strain events such as pipe ovalization due to highly anisotropic loading or formation strain anisotropy; and Pressure changes due to depletion of or injection into reservoirs. Identifying and quantifying these events early can help an operator remedy a potentially damaging production scenario, apply the correct seismic transit time correction during time-lapse reservoir seismic monitoring, or monitor production, injection, and pass-through zones for pressure depletion effects. We have installed, in an industry first, a high-resolution fiber-optic strain imaging system in a producing well. The theoretical, experimental and early deployment test trial details of this technology were reported in SPE 109941, presented at the 2007 SPE ATCE. In this paper, we will report high-resolution strain monitoring results obtained on a set of casing joints which were instrumented with several thousand fiber-optic strain sensors, deployed as a single fiber cable in an onshore production well, installed using normal rig equipment. Of particular interest at this early stage in the well's life is the demonstration of the strain measurement resolution and sensitivity, as evidenced by our ability to monitor the differential pressure between the inside and outside of the casing while circulating prior to cementing, during the cementing operation and while the cement was curing. This monitoring yielded excellent results while cementing the instrumented intermediate casing string, as well as while cementing the production casing string. Cemented at a measured depth of 8000 feet in an unconventional gas well, the strain-instrumented casing joints in conjunction with a distributed temperature sensor and external pressure gauge have continued to provide strain, temperature and behind-casing pressure readings through the remainder of the well construction, completion, hydraulic fracturing and the current, early production operations some six months after initial installation.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".