Parameter Evaluation of CO2 Sequestration Capacity in Depleted Oil Reservoirs - Coreflood Tests and Numerical Simulation
Bibliographic record
Abstract
Abstract CO2 sequestration in depleted oil reservoirs provides an appealing option for reducing CO2 emissions in the atmosphere. However, the available space in most depleted oil reservoirs for storing CO2 is quite limited because a large portion of the reservoir is occupied by the remaining water and residual oil. It is important to answer the question how to remove the remaining water and residual oil, thus maximize the capacity of CO2 storage in depleted oil reservoirs. In this paper, a comprehensive and systematic approach was taken to study the parameters affecting CO2 sequestration capacity in depleted oil reservoirs. Two groups of laboratory CO2 sequestration experiments were conducted at 59 °C and 5,500 kPa to study the effect of gravity on the CO2 sequestration process and provide history matching data for core-scale simulation. Orthogonal experiment analysis based on corescale simulation indicates that the three most important parameters for CO2 storage capacity are fluid flow direction, capillary pressure and reservoir pressure. Numerous simulation runs were conducted to investigate the detailed influence of fluid flow direction, capillary pressure, reservoir pressure, temperature, production rate, and injection timing. Simulation results indicate that CO2 should flow vertically and the roles of capillary pressure are different in cases of different fluid flow directions. Introduction CO2 sequestration in depleted oil reservoirs is among the most appealing options for reducing CO2 concentration in the atmosphere. Many reservoirs in Canada are potential candidates for CO2 sequestration[1–3]. However, the available space in most depleted oil reservoirs for storing CO2 is limited because the major portion of the reservoir is occupied by the water either injected during the recovery processes or invaded as a result of reservoir pressure decrease. The CO2 storage capacity in water as dissolved gas is much less than that of CO2 as supercritical gas. Meanwhile, the residual oil saturation after most tertiary recovery methods is still as high as 30%[4]. The remaining water and residual oil restrict the CO2 storage capacity in the depleted oil reservoirs. The objective of this paper was to evaluate the parameters affecting the storage capacity of CO2 from core scale experiments and simulations, thus to seek for methods to efficiently displace and produce water and oil retained in reservoirs after an enhanced oil recovery process. Many previous studies about CO2 injection are related to enhancing oil recovery rather than improving CO2 storage capacity[5–8]. Orr et al.[5] had a detailed discussion about mechanism of CO2 flooding for enhanced oil recovery, including swelling effect, viscosity reduction effect, and multiple-contact-miscible mechanism. The aim of those studies is to enhance oil recovery with the use of as little amount of CO2 as possible. However, CO2 sequestration is to sequestrate as much CO2 as possible safely in underground formations in a geological time frame. This process involves the balance of gravity force, viscous force and capillary pressure[9,10]. The methodology developed in this paper is important for both CO2 storage site selection and CO2 storage injection strategy in a candidate depleted oil reservoir.
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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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".