Heavy Oil Development: Summary of Sand Control and Well Completion Strategies Used with Multilateral Applications
Bibliographic record
Abstract
Abstract Multilateral drilling technology has been used in many heavy-oil developmental projects to achieve maximum reservoir exposure from a single surface location. The wellbore geometry and completion strategies for multilateral wells are planned and customized to fit the known reservoir characteristics and sand distribution qualities. Typically, heavy oil reserves are found in unconsolidated sandstone reservoirs that require some form of sand exclusion strategy across the reservoir as well as at the lateral mainbore junction interface. In heavy-oil sand, effective sand-control strategies must be carefully planned since one of the difficult problems to address in heavy-oil targets is their natural tendency to suspend formation solids, often referred to as Basic Solids and Water (BS&W) solids. An effective sand control strategy should allow these solids to be produced to surface and separated by the production facility. The remainder of the solids can be controlled, based on the sand-distribution qualities. If the formation sand is uniform, liner-only completions can be used for effective sand exclusion without sacrificing rate. If the formation sand is non-uniform, gravel packing will be required. For this reason, regardless of the well scenario, the gravel pack or liner only completion should allow BS&W solids to pass through and be produced to the surface. Most heavy oil development areas use artificial lift such as PCP and ESP pumps. All multilateral completion strategies must always consider the lift strategy, the ID requirements for pump deployment as well as necessary sand exclusion requirements for the pump. The paper examines successful multilateral completion strategies used in heavy-oil development projects in Canada, Trinidad and Venezuela. It will also explore new synergistic technologies that will impact future development strategies.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".