The Modelling, Application and Monitoring of Scale Squeeze Treatments in Heterogeneous Reservoirs, North Sea
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Scale control within produced fluids as water follows the cycle of injection, production, processing and reinjection in oil/gas production facilities is critical to the effective production of hydrocarbons in a safe, economic and environmentally acceptable manner. This paper will focus on the scale challenges associated with seawater injection into two North Sea reservoirs with a moderate Barium Sulphate scale challenge (80 to 220 ppm Barium, seawater injection) and will describe the impact of scale ion reduction from injection to production wells and the lower minimum inhibitor concentration that results The paper will outline the selection of the inhibitor chemical for squeeze application, initially via bullhead application of the squeeze treatment without diversion then development of a diversion methodology in conjunction with production logging tool data. The paper outlines the application of the diversion treatment applied via bull heading and the improvement in treatment life as well as treatment economics that resulted in the heterogeneous formation. The paper will clearly demonstrate using the four squeeze treatments to a single well how squeeze treatments can be enhanced without the need for coil tubing to allow selective placement. The design methods for this diversion technology will presented along with the methods of monitoring such treatment to ensure effective placement was achieved with the use of inert tracer, produced water analysis, evaluation of type/amount of suspended solids and inhibitor residuals.
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.
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 it