Bibliographic record
Abstract
Abstract Vertical Steam Flood Heavy Oil developments, such as Shell's Carmon Creek project, require a large number of wells. This high well count leads to the wells contributing a large part of the project cost and a large physical footprint. In the Carmon Creek project, the challenge for Shell was to safely drill and complete thousands of wells at the lowest possible cost while minimizing the footprint. The approach taken was that of a ‘Wells Manufacturing System’, using new technology, bespoke equipment and novel ways of working. The well construction operations were broken down in repeatable steps. This enabled fast learning and it provided the basis to engineer out ‘flat-time’ activities by designing fit-for-purpose equipment, such as BOP systems, wellheads and drilling rigs. Partnerships in low cost manufacturing locations were formed to build this equipment. A multi-disciplinary team designed wellpads, not only making them as small as possible, but also to enable the implementation of an assembly line philosophy. Three-dimensional well planning was crucial to establish the optimal well spacing at reservoir level. Drilling performance in similar developments was benchmarked extensively to be able to set challenging targets and to be able to measure performance. Given the application of the wells manufacturing system, using the same well design for both injector and producer wells was deemed most cost effective, since the key to the success of the manufacturing philosophy is repetition. This saves time and optimizes the supply chain. The resulting wellpad design has an unprecedented well count per pad of up to 49 wells, positioned in a single line. The well spacing was driven by how close beam pumps can physically be placed. The fit-for-purpose rigs have substructures that cover three wells simultaneously and function in essence as self-walking assembly halls, furnished with a super-single drilling mast. The rigs are equipped with double BOP's that can leapfrog. Work on three wells is performed simultaneously and activities such as BOP testing and waiting-on-cement are taken off the critical path. The rigs were built and operated by a Shell Joint Venture, blurring the boundaries between the traditional roles of operator, drilling contractor and Service Company, based on three principles: Build a Long-term relationship that allows Continuous Performance ImprovementTechnology that results in fit-for-purpose (FFP) equipmentVery attractive pricing that is not coupled to North American market volatility Drilling commenced in 2014 and performance has been excellent, particularly with learning by repetition exceeding expectations. The Project itself was cancelled due to political and economic reasons, but drilling on two pads was completed prior to the project halt. In total, 92 wells were drilled, with 65 wells achieving ‘Best in Class’ time and cost performance, and 77 Top Quartile wells. Well times and costs as a result decreased by up to 50%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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 source (direct Gemma or distilled Codex), 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".