Numerical Simulation and Screening of Oil Reservoirs for Gravity Assisted Tertiary Gas-Injection Processes
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Abstract
Numerical Simulation and Screening of Oil Reservoirs for Gravity Assisted Tertiary Gas-Injection Processes W. Ren; W. Ren Univerity of Alberta Search for other works by this author on: This Site Google Scholar L.B. Cunha; L.B. Cunha University of Alberta Search for other works by this author on: This Site Google Scholar R. Bentsen R. Bentsen University of Alberta Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago, April 2003. Paper Number: SPE-81006-MS https://doi.org/10.2118/81006-MS Published: April 27 2003 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Ren, W., Cunha, L.B., and R. Bentsen. "Numerical Simulation and Screening of Oil Reservoirs for Gravity Assisted Tertiary Gas-Injection Processes." Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago, April 2003. doi: https://doi.org/10.2118/81006-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Latin America and Caribbean Petroleum Engineering Conference Search Advanced Search AbstractCorefloods and field investigations confirm that a large amount of incremental tertiary oil can be recovered from dipping water drive reservoirs using gravity assisted tertiary gas injection processes. These processes include the Double Displacement Process (DDP) and the Second Contact Water Displacement Process (SCWD). The DDP consists of injecting gas into waterflooded oil zones. The SCWD process consists of submitting these gas-flooded zones to a new water displacement process.Reservoir simulations performed with an adaptive-implicit simulator were applied to investigate the macroscopic mechanisms of the two processes. The effects of several important parameters on the performance of the DDP were studied to optimize the oil production of the process and to develop a set of screening criteria for selecting candidate reservoirs for the process. Moreover, the SCWD process was simulated to investigate its feasibility. Furthermore, the two processes were simulated physically in a micromodel — transparent cell.The results have shown that both processes are efficient methods for recovering the residual oil to water. A good representation of the laboratory results was obtained through the simulations. It was confirmed that oil film flow plays a very important role in achieving high recovery efficiencies in the DDP. In the SCWD process, trapped gas reduces the possibility of the residual oil being trapped in the center of pores in the secondary water invasion. Consequently, residual oil can be recovered quickly by a second water flood. Therefore, the SCWD process is suitable for application in situations where the source of gas is not sufficient, and where the formation has a high irreducible gas saturation.IntroductionUp-dip gas injection into a dipping reservoir is one of the most efficient methods to recover waterflood residual oil. Recoveries of 85% to 95% of the original oil in place have been reported from field tests1,2,3, and higher, even up to 100%, recoveries have been obtained in the laboratory4. The idea of injecting gas to recover the residual oil after a waterflood appeared first in Carson's paper discussing a gas injection project in the Hawkins Field1. He named the process the Double Displacement Process, and defined it as the use of gas to displace a previously water displaced oil column. In the same year, Kantzas et al.4,5,6 showed in the laboratory that gravity drainage played a very important role in this gas injection process, and called it the Gravity Assisted Tertiary Gas Injection Process. They addressed the fact that reservoir wettability and spreading coefficient had a large impact on the gravity assisted tertiary gas injection process. Strongly water-wet porous media and a positive spreading coefficient are preferable in this process, and the process efficiency is dependent on the spreading phenomenon. Oren and Pinczewski7 studied the effect of the spreading coefficient on oil recovery using a network model. Their experimental results showed that oil recovery was significantly higher for positive spreading systems than it was for negative systems. Vizika and Lombard8 and Mani and Mohanty9 confirmed these results by conducting gas gravity drainage experiments in a sand pack and a network model.The incremental oil recovered by the DDP consists of two parts. The first part is the bypassed oil, which exists as a continuous oil phase in the regions of the reservoir unswept by water due to reservoir heterogeneity or well placement. The second part is the residual oil existing at the microscopic scale as isolated oil blobs in the water swept regions of the porous medium due to the capillary and surface forces. The gas injection process improves the sweep efficiency so that the bypassed oil is recovered. The trapped oil can be recovered by oil film flow. If the spreading coefficient of the oil is positive, when gas comes, the isolated oil blobs may form thin oil films. These oil films connect all of the residual oil in the gas swept zone to the oil bank, which is formed in front of the gas front soon after gas injection. The re-established hydraulic continuity of the residual oil provides channels (oil films) for the oil to flow through to the oil bank. When the oil bank reaches the production wells, both the bypassed oil and the isolated oil blobs can be produced. Keywords: gas injection process, scwd process, injection, oil saturation, upstream oil & gas, modeling & simulation, injection process, gas injection method, enhanced recovery, saturation Subjects: Improved and Enhanced Recovery, Gas-injection methods This content is only available via PDF. 2003. Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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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 | 0.001 |
| 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".