Novel Geophone Array Measures Exact Location of Fluid Movement Behind Casing
Bibliographic record
Abstract
This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 197560, “Enhanced Well Remedial Decisions From Exact Location of Fluid Movement Behind Casing Identification,” by Marcel Croon, SPE, Perry Huber, SPE, and Jacob Wright, SPE, Weatherford, SPE, prepared for the 2019 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 11-14 November. The paper has not been peer reviewed. Historically, acoustic wellbore monitoring is among the primary methods of detecting fluid movement behind the casing. However, analysis of the complex acoustic environment in the wellbore can be challenging. A standard hydrophone noise tool is unable to measure flow directions (vertical and horizontal) and cannot detect low flow, low-pressure sporadic events, or multiple sources. The complete paper discusses a geophone array, including four, three-component geophones deployed by wireline, that provides a solution for this problem by creating a 3D map of the acoustic environment. Introduction Well-integrity issues such as a poor cement bond can lead to undesirable fluid movements behind the casing, which could have negative effects with regard to health, safety, and the environment. A detailed understanding of annular fluid movement is critical in identifying potential source locations for wells with surface-casing vent-flow (SCVF) issues. Applicable scenarios include the following: Planned well-intervention activities for wells with multiple-source vent/flow situations Confirming the presence of flow (gas/oil/water) behind the casing Identifying areas with suspected crossflow between zones Integrity confirmation for gas storage caverns or zones Identifying unwanted flow for well-abandonment activities Well abandonment is bound by stringent regulations in some countries where the testing and repair of SCVF and gas-migration (GM) issues before final abandonment are required. An ex-ample is western Canada, where surface casing vents must be tested through a bubble test at minimum. This involves connecting a small container with 2.54 cm of water using fittings to the surface casing vent and monitoring for gas bubbles for 10 minutes. Often the flow rates are very low (less than 35 cu ft/d) with minimal pressure buildup. If bubbles are detected during the monitoring period, the well is deemed to have a positive vent flow. Consequently, the source of the vent flow must be identified by a survey as approved by the energy regulator, which could be conducted by means of acoustic logs, temperature logs, or gas- isotope analysis. Additionally, GM measurements must be conducted before final abandonment in specific areas within western Canada but are recommended for all wells. The complete paper details this process.
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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".