Process of Clastic Reservoir Facies Modelling Using Formation Micro-Images and 3D Visualisation Tools
Bibliographic record
Abstract
Abstract Predicting reservoir continuity in a siliciclastic reservoir is a challenge due to significant heterogeneities at all scales. In stacked channel and flood plain complexes, various lithofacies such as bedded mudstones, trough cross bedded sands and interbedded sands with mudstones associated with inclined heterolithic stratification.cause abrupt lateral and vertical variability in the flow path for reservoir fluids. This brings in the need for examining these facies variation using high resolution FMI* (Formation micro imager) log data which often mimics conventional core facies. In addition, it provides valuable data such as paleocurrent directions. This unique workflow proposes an integrated approach of combining core calibrated formation micro image facies, paleocurrent data and synthetic resistivity (which augment the signature of a regular geophysical log suite), differentiating some key lithofacies and finally populating a 3D grid with the measured parameters applying a combination of deterministic and stochastic property modeling techniques using Windows? based Petrel* Workflow Tools. These data provide the basis for reservoir characterization and minimization of risk through effective well planning. Introduction A predictive model for identifying reservoir quality in a portion of the EnCana Foster Creek in-situ oil sands project in northeastern Alberta is presented utilizing stratigraphic property modeling and visualization in three dimensions. Production is obtained by Steam Assisted Gravity Drainage (SAGD), which requires a detailed understanding of the reservoir (Figure 1). Data currently exists on over 600 vertical delineation wells, 80 cored wells and 300 borehole image logs (Formation Micro- Imager*-FMI). This paper illustrates a process through which clastic lithofacies and synthetic resistivity logs determined from some pilot well borehole images and cores could be propagated in 3D space using a combination of deterministic and stochastic property modeling in Windows? based Petrel* Workflow Tools. These aid in understanding reservoir continuity and thereby reduction of risks associated with well placement and hydrocarbon recovery. Imaging clastic reservoirs The Formation Micro-Imager* (FMI) is a 8 pad azimuthal borehole electrical imaging device developed by Schlumberger. It is an extension of dipmeter technology and has 192 scanning electrodes arranged in 24 electrodes per pad/flap arrays (of four pads and four flaps) which are used to provide a high spatial sampling of formation microconductivity in both the vertical and azimuthal directions on the borehole surface. A General Purpose Inclinometry tool is also run along with this service to calculate hole azimuth and relative bearing in order to orient the measurements with respect to north and the borehole. These two-dimensional microresistivity data are then processed; depth matched with other open hole log data and mapped to color scale to produce "core-like" borehole wall images that allow fine scale geological features to be described with a very good vertical resolution of about 0.2inch (5mm). Two types of processed images are common. Static normalized Images are obtained through processing of the entire logged interval and allocating colors whereby brighter colors indicate high resistivity and darker colors indicate lower resistivity using a histogram technique.
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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 | 0.001 |
| 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".