Analyzing Transient Pressure and Rate Responses of Tight Oil Reservoirs Using Comparative Numerical, Analytical and Semi-Analytical Methods
Bibliographic record
Abstract
Abstract Low to ultra-low permeability tight oil reservoirs have recently become a significant source of hydrocarbon supply in North America, Production and pressure transient analysis of tight oil reservoirs is one of the most difficult problems facing a reservoir researcher because of the extreme complexity inherent in tight formations, To produce oil and gas commercially from tight formations, naturally completed (open-holed) or cased horizontal wells with multi-stage hydraulic fractures are the most popular implementation for completion, and such kind of application is expected to create a complex sequence of flow regimes (Chen and Raghavan, 1997; Clarkson and Pederson, 2010). The proper analysis and identification of presence of flow regimes and sequence of emerging flow regimes are essential for obtaining efficient information about hydraulic fracturing optimization and the tight formation characterization. This paper provides a detailed discussion of numerical method of pressure transient and rate responses for hydraulically fractured horizontal wells in tight formation and compared with analytical (semi-analytical) methods based on the Bakken and Viking Formation in Western Saskatchewan. For Numerical simulated pressure transient responses, a naturally-completed (open-hole) and cased horizontal well with multiple transverse hydraulic fractures in a homogeneous or a sizable natural fracture system are considered. Numerical method for pressure and rate transient analysis is generated by employing a commercial reservoir simulator, CMG IMEX, a 3D finite-difference reservoir simulation package which is widely and popularly accepted by petroleum industry. As noted by many findings, it is shown that fully-filled and regional natural fractures would display various pressure transient characteristics and, hence, considerably affects well production performance. In addition, these conductive, interconnected natural fractures dominate the pressure transient performances of horizontal wells in tight formations even with the presence of hydraulic fractures. Additionally, the simulation runs also indicate that if the reservoir is naturally fractured to some extent, hydraulic fracturing stimulation might not improve productivity significantly, unless a large amount of hydraulic fractures and infinite conductivities can be achieved. To demonstrate the feasibility of numerical simulation models, there is a representative contrast between numerical and analytical (semi-analytical) methods. To demonstrate the feasibility of numerical simulation models, there is a representative contrast between numerical and analytical (semi-analytical) methods.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".