LiDAR Technology as a Means of Improving Geologic, Geophysical and Reservoir Engineering Evaluations: From Rocks to Realistic Fluid Flow Models
Bibliographic record
Abstract
Abstract Outcrops of the Milk River Formation (sandstone, Cretaceous age) at the Writing on Stone Provincial Park in Alberta, Canada have been scanned using ground LiDAR (light detection and ranging) technology. Milk River outcrops represent a real 3D challenge for this technology because of the complexity of hoodoos emanating from pronounced erosion in the area as a result of wind, water and ice following the melting of ice at the end of the last ice age. In addition to the 3D complexity of the hoodoos, the Milk River Formation at Writing on Stone was selected for this project because the geology, studied in detail previously, is characterized by intervals that include a range of sand-rich lithofacies, and is distinguished primarily by subtle differences in grain size and current structures of the sandstones. Also present in the area are relatively flat 2D cliff faces and subvertical fractures. The outcrop exemplifies a challenge for realistic fluid flow modeling. This is of practical importance because these types of rocks develop significant hydrocarbon reservoirs in the Western Canadian sedimentary basin and throughout the world. When buried significant volumes of gas can be trapped in tight formations of similar age. This paper describes an evaluation sequence that includes the planning for LiDAR data collection, actual work and rock sample collection in outcrops, the interpretation and integration with geoscience in a 3D visualization room, and the potential for improved drilling and completion techniques, and reservoir simulation by using the concept ‘from rocks to realistic fluid flow models’. It is concluded that LiDAR provides a powerful technique for sound interpretation of reservoirs rocks and their integration with other sources of information. Introduction The present study was undertaken to test and evaluate the capabilities and limitations of ground-based laser scanning technology (LiDAR) for the construction of reservoir models based on surface outcrops. A multidisciplinary team of the University of Calgary has embarked on a project to investigate and better characterize tight gas/fractured reservoirs, in which the study of outcrop analogues is an integral part. The multidisciplinary research project is called GFREE, an acronym that stands for the integration of geoscience (G), formation evaluation (F), reservoir drilling, completion and stimulation (R), reservoir engineering (RE), and economics and externalities (EE). Before investing heavily in expensive, up-todate LiDAR hardware and software, and in the time and effort of researchers, a pilot study was deemed to be necessary to evaluate the feasibility and usefulness of LiDAR-based mapping/imaging methods. The University of Calgary and the University of Texas at Dallas joined forces to achieve this objective. Herein we report on this pilot study of the various phases in the use of LiDAR, that is, data acquisition, data and image processing, and possible qualitative and quantitative applications of the resulting model. The rocks chosen for the pilot study are the Virgelle Member sandstones at Writing-on-Stone Provincial Park (WOS) in southern Alberta, an area with relatively continuous, superbly exposed outcrops along the Milk River valley.
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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 | 0.000 |
| 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".