Cold Flow: A Multi-Well Cold Production (CHOPS) Model
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Bibliographic record
Abstract
Abstract A multi-well cold production (CHOPS) model, developed at the Saskatchewan Research Council, was used in conjunction with a commercial reservoir simulator, to predict the effect of well spacing and in-filling on oil recovery in cold production. The oil and sand production from the Lindbergh/Frog Lake cold production wells was history matched initially. The comparative economics of five different well spacings (10 acre, 20 acre, 40 acre, 60 acre and 80 acre) was estimated. The 20 acre spacing was the most economic overall for heavy oil prices varying between C$251/m3 (C$40/barrel) and C$502/m3 (C$80/barrel). The multi-well model was used to estimate the additional oil recovery from in-fill wells at different in-fill times. In-filling a 40 acre spacing well with 10 acre spacing wells was not economic for a Lindbergh/Frog Lake type of reservoir. In-filling the same well with 20 acre spacing wells was economic at higher oil prices in the C$502/m3 range (C$80/barrel). Introduction The main mechanisms which contribute to the success of the cold production process are solution gas drive and sand production. Maini(1) argued that the greater oil recovery for heavy oil compared to light oil was due to the formation of a gas in oil dispersion which he called "foamy oil." This dispersion would have a greater compressibility which would maintain the reservoir pressure for longer times. Firoozabadi(2), based on a series of solution gas drive experiments performed at reservoir-type oil velocities, attributes the greater oil recovery for heavy oil to a higher critical gas saturation and to reduced gas flow leading to reservoir pressure maintenance. Three basic scenarios were proposed in the literature to explain how sand production leads to greater oil recovery:a limited dilated sand region around the wellbore(3),a dilated sand region around the wellbore with wormholes extending into the formation(4) andonly wormholes extending out into the formation(5, 6). The third scenario can best explain the rapid (within a few hours) travel time of a fluorescein tracer dye between an injector and a producer, observed by Amoco in a tracer test(5). Since the concentration of this dye, which is known to adsorb on the surface of a porous medium, did not change at the producer, Squires(5) concluded that an open (sand-free) channel connected the injector and producer. This observation contradicts scenarios 1 and 2 since these scenarios preclude the existence of an open channel throughout the length of the wormholes. Field engineers have observed that they sometimes lose fluid circulation while drilling into cold produced reservoirs. The location at which fluid loss occurs can help in mapping the wormhole network in the field. For example, when Nexen Inc. drilled two horizontal wells in a field after cold production, they observed lost circulation to neighbouring wells at the locations indicated by the ? marks in Figure 1. These 40 acre spacing cold production wells had produced large quantities of sand.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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