A Successful Story of Integration Geological Characterization, Reservoir Simulation, Assisted History Matching and EOR in a Giant Fractured Granite Basement: A Road Map to Maximize Recovery in Unconventional Reservoirs
Bibliographic record
Abstract
Abstract Near shore oil reservoirs have become significantly depleted, forcing oil companies to explore the unconventional reservoirs with huge investments and the latest technology. Among them, naturally fractured reservoirs (NFR) are found throughout the world and contain significant amount of oil reserves. Because of the unique of a NFR, there are lots of uncertainties in exploration and field development of these complex reservoirs. White Tiger is the biggest fractured basement reservoir up to now on the continental shelf of Viet Nam and even the world. This reservoir has a very complicated geological structure; high temperature (more than 2840F) and closure stress (more than 6,000 psi). The total OIIP of this field reached nearly 4 billion barrels with 6,561 feet of the oil bearing thickness in granite basement and has been produced by more than 200 wells, with production rate of 180,000bbls/d. Due to the challenges of geology, these are essential to have successful operations as well as reducing uncertainties and improving the efficiency of oil field management. With a large database collected from initial production stages, the authors developed an integrated static and dynamic workflow to forecast oil production under several production scenarios for this reservoir. A successful assisted automatic history matching approach was proposed by combining global and local optimization which could be effectively accelerate the convergent problem and minimize computation mass of inverse problem, to construct a reliable model for complex reservoirs. Then, a series of compositional reservoir model were performed and analyzed by CMGTM simulator in order to evaluate the possibility of polymer flooding in fractured basement reservoir. The results showed polymer flooding would become an excellent candidate for enhanced oil recovery. Additionally, polymer retention phenomenon by adsorption on the rock surface and precipitation by high salinity was deeply investigated. An optimum range of important factors were determined to reduce the effect of chemical adsorption, it helps minimize mass of chemical loss and improve economic efficiency of chemical flooding process. Introduction A reservoir fracture is a naturally occurring macroscopic planar discontinuity in rock due to deformation or physical diagenesis (Nelson, 1985). A great portion of the world's oil reserves is contained in naturally fractured reservoirs (NFR). In NFRs, fluids exist in two interconnected systems: the rock matrix, which usually provides the bulk of the reservoir volume, and the highly permeable rock fractures. Fractured basement reservoir is a special type of NFR which is commonly very thick and the distribution of porosity and permeability is irregular. In the past, fractured basement reservoirs were often considered uneconomic. Recently, due to the increasing knowledge of basement plays and the demonstration of successful cases around the world, fractured basement reservoirs are becoming increasing attractive for exploration. Although oil production from basement rocks is not a common occurrence worldwide; but, there is significant oil production from such reservoirs in a number of countries
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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 | 0.001 | 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)
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".