Upscaling of Oil-Water Displacement in Naturally Fractured Reservoirs
Bibliographic record
Abstract
Abstract The objective of this study is to develop an upscaling methodology for simulation of oil-water displacement in fractured porous media. The "real response" is determined from 2-D fine grid models that explicitly incorporate given fracture distributions. The fine-grid models are used to determine equivalent properties of the fractured systems, which, when included in conventional double porosity models, will result in a behavior similar to the fine-grid response. The upscaling methodology is based on flow simulation with constant pressure and constant flux boundary conditions. The upscaling parameters of each equivalent double-porosity grid are determined by matching results of the fine grid simulation. The effects of some important factors such as the grid size of the upscaled model, injection rate, and well location are examined to test the generality and accuracy of the upscaling methodology. Introduction Geological characterization of fractured reservoirs has progressed considerably in recent years, allowing for realistic representation of fracture networks. Despite advances in reservoir simulation and computer hardware, such detailed geostatistical results cannot be used directly in the simulation of fractured reservoirs. Up-scaling techniques are needed to translate the geostatistical data into reservoir simulation parameters. There are several upscaling techniques .(1–4) used in the simulation of single-porosity reservoirs to reproduce the details of small-scale fluid mechanics and reservoir heterogeneity in coarse-grid models. However, there is no general procedure that is widely accepted for upscaling. The upscaling methods for naturally fractured reservoirs are further behind. Based on the type of fracture system, the upscaling study of naturally fractured reservoirs can be divided into two categories: the single continuum, and the dual continuum approach. For the single continuum approach (5–7), the system is considered as a heterogeneous matrix system with discrete fractures. Various methodologies, such as the boundary element and finite volume methods, are widely used to deal with complex fracture systems. Most single continuum methods consider single-phase upscaling only, and treat the upscaled permeabilities as tensor terms. The dual continuum approach (8–11) is based on the double porosity model of Warren (12) and Root, and its representation in the simulation of fractured reservoirs (13, 17). The dual continuum upscaling therefore requires determination of the properties required for double porosity simulation of the fractured system. Most of upscaling research concentrates on obtaining equivalent properties for a single-porosity simulation of afractured system. Upscaled single-porosity models do not exhibit some of the important characteristics of naturally fractured reservoirs. In particular, a singleporosity model cannot distinguish between the fluid fronts in the fracture and the matrix. The doubleporosity approach, however, includes a formulation for modeling unsteady-state multiphase fluid exchange between the matrix and the fractures. In this work, we will obtain the equivalent double-porosity parameters for oil-water displacement in a fractured porous medium. In the following, the upscaling framework, including the fractured systems used in our study, is presented first. The upscaling methodology and results are then described in detail. UPSCALING FRAMEWORK Water displacement in double-porosity systems can been visioned as multi-phase flow through fractures along with fluid transfer between the fracture and the matrix.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".