TINBOP Cyclic Steam Injection Enhances Oil Recovery in Mature Steamfloods
Bibliographic record
Abstract
Abstract In a previous paper (SPE/PS-CIM/CHOA 97850), we presented our findings on a novel cyclic steam injection method that we developed. The Top-Injection Bottom- Production (TINBOP) method consists of injecting steam in the short string and producing fluid from the long string of a well. Our simulation study shows TINBOP increases oil recovery by 57–93% compared to that with conventional cyclic steam injection. In this paper, we present results of our simulation study that compares TINBOP cyclic steam injection against steamflooding, using typical properties of the mature Lombardi reservoir, San Ardo field, California. The field contains heavy oil of 11 °API and insitu viscosity of 3000 cp. A 30?30?20 Cartesian model is used that represents one-eight of a 10-acre inverted 5-spot pattern. A total 37 years are simulated: 17 years under natural depletion followed by 20 years steamflooding or 20 years TINBOP (with the same amount of steam injected). Simulation results indicate TINBOP cyclic steam injection enhances oil recovery to 76% OOIP compared to that with conventional steamflooding, 69% OOIP. The workover cost to convert an existing well to a TINBOP well appears relatively small compared to the gain in oil recovery. Introduction Heavy and extra-heavy oil resources are estimated to be more than 2.5 trillion STB. The vast resources of the Orinoco and Canada extra-heavy oil or bitumen regions are well documented, and offer large targets for in-situ and surface ecovery techniques. Potential recoverable heavy and extraheavy is estimated to be 856 MMSTB with current technology. There are two forms of steam injection, steamflooding or steam drive, and cyclic steam injection or stimulation (CSS) or huff-and-puff. In steamflooding, steam is continuously injected into fixed well patterns of injection wells, while fluids are produced in designated wells. Depending on the reservoir properties and pattern, steamflooding oil recovery factor may be as high as some 60% of original oil-in-place (OOIP) [1]. In cyclic steam injection, the primary objective is to reduce the oil viscosity near the vicinity of the wellbore. Oil recovery factors with CSS are generally lower, typically less than 15% OOIP [1]. Steam Over-Ride The main factor that adversely affects oil recovery under steamflooding is steam over-ride, particularly in mature steamfloods. As shown in Fig. 1, as a result of gravity segregation, the injected steam quickly rises to the top of the reservoir, by-passing the oil below it [1]. The steam is preferentially produced at the production well because of its significantly lower viscosity. In mature steamfloods, the overlying steam region (steam chest) may extend throughout the field. Only a thin layer of oil near the oil-steam interface is directly heated by the steam. This heated oil layer then slowly drains to the production well by gravity. Steam-override is practically unavoidable. The objective of steam management is to maximize oil recovery and minimize steam injection cost. How can we accelerate and increase the recovery of the "cold" oil underlying the steam chest? We have developed a novel method (TINBOP) which attempts to do exactly this.
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How this classification was reachedexpand
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 | 0.001 | 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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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