The Thermal Recovery Methods and Technical Limits of Bohai Offshore Heavy Oil Reservoirs: A Case Study
Bibliographic record
Abstract
Heavy oil accounts for a large proportion in offshore petroleum reserves. For Bohai offshore oilfield in China, about 85% of the OOIP is the heavy oil. Heavy oil has become an important form to guarantee the offshore oil production. Considering the limited space in offshore oil platform, cold production method is the commonly-used development method. But for some heavy oils with higher viscosity (>350cp), cold production method is less effective, and thermal recovery process will be a better choice. In this paper, we focuses on three different heavy oil reservoirs from Bohai offshore oilfield, including the blocks of NB35-2, LD-1 and LD-2. These three blocks essentially represents the main heavy oil reservoir types of Bohai oilfield (edge-water, bottom-water and thick oillayer). Then through the analogical analysis between onshore reservoirs and offshore reservoirs, the development methods for the three blocks are determined firstly. In this process, we make a survey on the development status of onshore heavy oil reservoirs in China. Then, based on the geological properties of the three blocks, a set of numerical simulation runs are performed to analyze the influence of many sensitive factors (e.g., reservoir depth, thickness, permeability, net-to-gross and water-zone). After that, through the computation of net present value (NPV), we reevaluate the economic limit indexes of thermal recovery process in Bohai offshore heavy oil reservoirs and determine the technical limits. From the analogical results, it is concluded that different heavy oil reservoir will have different thermal recovery method. For the three heavy oil reservoirs, cyclic steam stimulation (CSS) process is a potential EOR method for block LD-1, and steam flooding is a better choice for NB35-2, and LD-2 could adopt the methods of steam flooding process and SAGD process. From the numerical simulation results and NPV results, we found it is not economical to perform a CSS process in LD-1. For the other two blocks, NB35-2 and LD-2, the economical cumulative oil-steam ratios under the corresponding thermal recovery methods are calculated. And the technical limit of thermal recovery process in Bohai offshore heavy oil reservoirs are derived. It shows that a steam flooding process is suitable to the edge-water heavy oil reservoirs in Bohai oilfield whose heterogeneity is relatively weak, formation is relatively thin (10m
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".