Transient Analysis of Sandface and Wellbore Temperature in Naturally Fractured Geothermal Reservoirs: Numerical and Analytical Approaches
Bibliographic record
Abstract
Abstract This work presents the numerical and analytical temperature solutions that couple the transient reservoir/wellbore thermal models to analyze the temperature measurements recorded at producing horizon or at a certain gauge depth above it for estimating the physical and thermal properties of naturally fractured geothermal reservoir (NFGR) during drawdown and buildup periods. The NFGR is replicated by a more general triple-porosity system adopted from Abdassah and Ershaghi model. We first develop numerical and analytical solutions to predict the sandface temperature in NFGRs, accounting for the Joule-Thomson (J-T) effect, adiabatic heat expansion/compression effect, heat convection and conduction. The developed numerical solution is verified and found to agree with the proposed analytical solutions. Then, the wellbore heat flow model adopted from Hasan and Kabir model is coupled with NFGR model to predict the wellbore temperature at a certain gauge depth above producing horizon. The results show that three heat radial flow regimes and two thermal inter-porosity regimes have been identified. It is demonstrated that the early-time heat flow is dominated by the adiabatic heat expansion/compression effect, and the intermediate- and late-time heat flows are dominated by J-T heating/cooling effect. It is demonstrated that thermal properties such as J-T coefficient, adiabatic heat expansion coefficient and fracture intrinsic porosity can be estimated through temperature transient analysis, which are not accessible by pressure data. The results also show that when the gauge location is near the producing horizon, the heat transfer regimes keep almost identical to sandface during drawdown period. As the distance between the gauge location and producing horizon increases, drawdown-wellbore temperatures are more dominated by wellbore heat loss, thereby may miss some information contents from reservoir. Moreover, buildup-wellbore temperatures are usually dominated by wellbore heat loss and do not exhibit any discernable flow regimes even though gauge location is near the producing horizon. It is demonstrated that wellbore temperature derivative exhibits unit slope at early times for drawdown and buildup periods. Finally, we develop an integrated semilog-straight-line analysis workflow of combining sandface pressure and temperature data to estimate NFGR properties. Synthetic test example is interpreted to demonstrate the applicability of the developed workflow.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".