Is Waterflooding the Clearfork Viable? Using Reservoir Simulation and Analog Data to Overcome High Uncertainty
Bibliographic record
Abstract
Abstract Potentially generating an estimated $1.3 million in net present value, a proposed pilot waterflood in the Permian Basin of West Texas was determined to be technically and economically viable by using a reservoir model and analog data. Located in Winkler County, the lease has produced conventionally from various formations since its discovery in 1944. Primary production from the prospective waterflood interval, the Clearfork, began in 1994, and the daily oil rate has since declined 95%. At the current decline rate, commodity price, and operating expenditure, the lease is expected to become uneconomic by Spring 2017. An analysis was conducted to determine the technical and economic viability of implementing a waterflood of the Clearfork formation to extend the life of the lease. A reservoir model of the field was created and history matched to validate reliability before predicting reservoir response to the pilot waterflood. A secondary independent analysis used an offset operator's Clearfork waterflood as an analog to generate a production forecast using dimensionless curves, and the results confirmed the numerical model forecast. The predicted reservoir response using both methods revealed that implementing this project would result in over 40 MBO net reserves per producer. Economic analysis indicated that the project would be viable at $51/bbl oil price.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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".