Distributed Acoustic and Temperature Sensing Applications for Hydraulic Fracture Diagnostics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Hydraulic fracturing operations in unconventional reservoirs are increasingly being monitored with fiber-optic (FO) Distributed Acoustic and Temperature Sensing (DAS/DTS). In this paper, we discuss how a single well equipped with fiber optics and DAS can be used as a diagnostic tool to better understand the completions program of three offset wells and the fiber instrumented well. Strain measurements were initially conducted for seismic studies, then followed by measurements of fluid injections from monitoring wells to better understand placement along the lateral section of the wellbore for programs such as hydraulic fracturing, water flooding, and steam injection. The broadband DAS signals have shown of value for the monitoring of microseismic, as well as thermal and mechanical strain of the fiber over the entire well-pad's completion process. During well stimulation, as a fracture propagates to an offset wellbore with fiber deployed, the DAS measurements can be used to monitor very small changes of strain on the fiber. Analysis of the Cross-Well Communication (CWC) strain measurements provide information about possible fracture numbers and locations, as well as the fracture propagating rate based on known well distance. Changes in the strain measurements are coupled with microseismic events that can be simultaneously monitored using the same interrogator unit and fiber optic cable. Here we present various diagnostic tools for DAS that help to better understand the completions program. A variety of physical effects, such as temperature, strain and micro seismicity are measured and correlated with the treatment program to aid in the analysis. Two of the offset wells were zipper-fractured first, then the fiber installed well was zipper-fractured with the third offset well. By monitoring CWC strain measurements we show that DAS can assess the treatment and performance of neighboring wells that are not instrumented with fiber optic cable. Low frequency strain events from neighboring wells provide direct measurements of the fracture density and possible fracture network post fiber well completion. CWC measurements can provide strain levels that can be analyzed in the context of the various completion parameters including stage length, clusters, and well spacing, etc. We also discuss the fluid and proppant allocations measurements that can be performed on the well with fiber installation. We show how DAS can be used as a tool for investigating cluster efficiency, diverter effectiveness, and for determining completions problems like screen-outs and stage communication. The analysis of the DAS data demonstrates that current fiber-optic technology can provide enough sensitivity to detect a significant number of frac events that can be used for an improved reservoir description and as an assessment of the completions program.
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.
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 it