Basin Modeling in Complex Area: Examples from Eastern Venezuelan and Canadian Foothills
Bibliographic record
Abstract
Basin modeling aims at reconstructing the time evolution of a sedimentary basin in order to make quantitative predictions of geological phenomena leading to hydrocarbons accumulations. It accounts for porous medium compaction, heat transfer, hydrocarbon generation and fluid flow. Nevertheless, classical basin models handle simple geometry and are not usable in complex geometry area such as foothills. This is why, a numerical prototype Ceres, has been developed. This prototype is able to model three-phase flow in a 2D section of a basin, whose geometry changes through time accounting for deposition, compaction, erosion of the sediments, salt or mud creeping, and block displacement along faults. The classical flow chart to perform a case study is composed of three main steps. The first step is the building of the present day section. This is generally done with data coming from the seismic interpretation, wells, outcrops, and core data. At this stage, the section is generally balanced using software such as Locace. The second step is the restoration of the section. The section at present day is restored back in the past for each of the defined layer until the substratum is reached. In order to balance the section during time and to constrain the eroded parts of the section, we have to use a forward kinematic modeling tool such as Thrustpack. Thus, from a section restored with Locace before thrusting, the use of Thrustpack allows to construct intermediate sections during time, which are consistent from a kinematics point of view. The last step is the forward simulation. And, in order to solve the coupled equations that are generally used in basin models, we had to develop original numerical methods based on domain decomposition techniques. The previous methodology is the fruit of tests performed for an Alberta (Canada) transect and an eastern Venezuelan transect. When considering the origin of the fluids in the Oligocene sandstones of the El Furrial structure or in the Mississipian dolomite of the Canadian foothills, a general scenario of squeegee fluids is recognized. Before the flexuring and thrusting period, fluids are in equilibrium with the sediments. They are being continuously expelled toward the surface during the compaction related dewatering. Then, because of the tilting and thrusting with the deposition of synflexural sediments, an episode of squeegee fluid is created with flow along the stratification that can reach velocity of tens of kilometers per million of years. This squeegee episode stops when the thrusts of the considered area become active.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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".