Characterization of Reservoir Heterogeneity Based on Performance of Infill Wells in Waterfloods
Bibliographic record
Abstract
Abstract Reservoir heterogeneities are known to influence success or failure of infill wells in waterfloods, but no satisfactory ways currently exist for their characterization, quantification, or prediction. In 1950, Dykstra and Parsons(1) presented empirical correlation for waterfloods in certain California reservoirs based on observed variations in permeability. In general, procedures for most reservoir engineering predictions could be greatly improved if heterogeneity could be characterized by one or more terms. However, it is painfully obvious that because of the multitude of reservoir descriptions encountered in any oil prone basin, a single parameter (or a small number of parameters) may not be adequate. This is because of different ways in which heterogeneity impacts the performance of vertical or horizontal infill wells placed to enhance production/ reserves in a variety of waterflood situations. It is postulated that reservoirs are divided into predominantly horizontal or vertical "compartments" due to spatial variations in reservoir attributes such as permeability, thickness, environment of deposition, and post-depositional changes. Oil contained in these compartments, though often not strictly isolated, is not easily contacted or displaced by the injected water. Alternately, flow within the reservoir might be predominantly through certain pathways, some of which might involve cross-flow between various regions or intervals. Horizontal wells do a better job of draining oil than vertical wells in certain situations and vice versa. This paper proposes a method for characterizing reservoir heterogeneity and illustrates its application via four case studies of infill wells in waterfloods in the Western Canadian Sedimentary Basin (WCSB). Comparative performance is presented for infill horizontal and vertical wells placed in these projects during the past 15 years. Introduction In waterflood recovery projects, recovery at any point in time is a product of displacement efficiency, conformance (vertical sweep efficiency), and areal sweep efficiency. Whereas conformance can be estimated using Dykstra-Parson's procedures(1), sweep efficiency largely depends on areal heterogeneity in different intervals, besides factors such as mobility ratio, injected fluid throughput, and flood pattern geometry(2). Effects of areal heterogeneity have largely been approximated by "fudge factors," in the absence of a quantitative methodology for estimating them. Here, we propose an alternate method of characterizing areal or lateral heterogeneity in waterflood projects, based on performance of infill vertical and/ or horizontal wells. Areal or lateral heterogeneity can be characterized using the following data (whenever available):Suitable geological analogs (outcrops or sub-crops as revealed in quarries or mines(3), or logs/cores);Results of pulse/interference tests between various injectors and producers;Inter-well tracer returns data for the specific waterflood project, provided sufficient amount of data are available for various injectors and producers(4); and,Performance of different production wells (vertical and horizontal). Infill vertical or horizontal wells are drilled to reduce interwell spacing and modifying flooding patterns in drive situations, thereby accelerating production, improving volumetric sweep, and recovering some of the otherwise unrecoverable oil(5–7) from individual target locations.
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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 | 0.003 | 0.001 |
| 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".