Design Methodology for Selection of Horizontal Openhole Sand-Control Completions Supported by Field Case Histories
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Bibliographic record
Abstract
Summary Reservoirs requiring sand control pose a major challenge for selecting a suitable completion method. Horizontal openhole completions have been successfully used in such reservoirs to eliminate sand production while maximizing productivity/injectivity and well deliverability throughout the expected life of the completion and minimizing risk and complexity. Although horizontal, openhole, sand-control completions, ranging from preperforated/slotted liners to gravel packs, have been applied widely in the last decade and many case histories have been discussed in the literature, a systematic methodology for selecting these completion methods remains to be documented. It is the objective of this paper to propose such a design methodology by unifying the broad experience and understanding from a global, technically integrated perspective. The paper first discusses a generalized and unified methodology for determining when to install sand control, what to install for sand control, and how to install it in horizontal openhole completions. Specific factors recognized as affecting "when" are in-situ stresses, pore-pressure decline (sand prediction), expected well life, production rate, hydrocarbon and well type, gross product value, sand tolerance capacity, environmental limitations, and intervention capabilities, while the integration of all these factors has an impact on the overall risk analysis. In addition to many of the previous factors, critical drivers affecting "what" are identified as wellbore architecture, reservoir lithology and petrophysical properties, and sandface equipment reliability. Additional parameters impacting "how" are reservoir drilling fluid, displacement and cleanup methodology, screen type, operational implementation/ assurance (risk management, operational timing, and location logistics), torque and drag analysis, and gravel-placement simulations. Secondly, examples of this methodology are presented in detailed case histories pertaining to different types of horizontal, openhole, sandface completions, including slotted liners, standalone screens (including expandable), and gravel packs, as well as various integrated cleanup methods, along with a summary of the lessons learned by each company.
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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 | 0.000 |
| 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