Factors That Impact the Performance of Resin Coated Proppant in Low Temperature Reservoirs
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 Pumping a tail stage of resin coat proppant (RCP) is well documented method to control proppant flowback in a wide variety of oil and gas wells. The performance of RCP can be impacted by reservoir temperature and closure stress, as well as fluid and fracture placement parameters. RCP systems were originally designed for higher temperature applications although the use of lower temperature curable resins in shallow lower stress reservoirs has been discussed since at least mid-2005. 1,2,3 Strong oil prices and relatively weak gas prices have recently (2012) been driving the development of relatively shallow tight oil reservoirs within the Western Canadian Sedimentary Basin (WCSB) including the Slave Point, Cardium, Bakken, Viking and others. These reservoirs typically have relatively low reservoir temperatures and closure stresses which highlight the importance of looking beyond the reservoir temperature with a holistic evaluation of the fracture fluid interactions and fracture placement efficiency that can significantly impact RCP placement and performance; existing SPE publications also provide good background to the impact of these contributing factors.4,5 Most RCP literature focuses on clastic applications. In conjunction with our proppant supplier and pumping service partner, Lone Pine Resources Canada Ltd (LPR) has recently conducted laboratory testing designed to optimize the use of RCP within the Slave Point carbonate reservoir that LPR is successfully developing with multi-fractured horizontal wells (MFHZ). The Slave Point reservoir presents a challenge to RCP performance with a combination of a cool reservoir temperature of 40°C (100°F) and low closure pressures of roughly 20 MPa (2,900 psi). During Q1/Q2 2012 LPR identified a proppant flowback that was inhibiting production and increasing workover expenditures. Study of the problem identified proppant mixing and a lack of RCP bonding as root cause issues. A holistic review of the LPR Slave Point fracture program resulted in significant changes to the fracture treatment design and execution including the RCP type, resin activation parameters and base fluid changes. LPR has been able to minimize proppant flowback to the point that bottomhole pump failures as a result of proppant production have been significantly reduced, if not eliminated, and no incremental proppant clean-out operations have been required since the implementation of an optimized fracturing program that includes higher viscosity fracturing fluid and an optimized RCP-LT and activator program. In addition, no measurable proppant flowback volumes have been recovered during initial CT clean-out from the last four July 2012 fractured wells. These are very positive indicators that the RCP-LT and activator changes, improved fracture fluid viscosity and proppant placement has solved the proppant inflow problem.
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