Acid-Fracturing Techniques as a Good Alternative to Help Improve Field Development Assets
Bibliographic record
Abstract
Abstract Acidizing and acid fracturing techniques are routinely used in two important formations in the marine regions of Mexico, the Jurassic and Cretaceous formations. These formations are naturally fractured carbonate and dolomite reservoirs having a permeability in the range of 0.19 to 22 mD, porosity from 2.8 to 6%, approximate bottomhole temperature (BHT) up to 177°C, pressure (BHP) of 10,374 psi, and a crude of 45° API. Using acid fracturing techniques helps improve the development of these assets. This paper shows the results of more than 40 acid fracturing operations performed in recent years. Depending on the productivity evaluation, wells belonging to these assets are stimulated as part of the completion stage. Because of their low permeability, a common approach is to perform an acid fracturing operation. As a first evaluation, a minifrac test is executed to obtain the necessary data to calibrate the acid fracturing simulation model. After this step is performed, the acid fracturing design is evaluated. Generally, a sustained production acidizing technique is used for conductivity enhancement and closed-fracture acidizing is also included as a tailored treatment with an all seawater-based acidizing system. For these operations, an average five-fold increase in oil production has been observed after treatment. In some cases wells in the completion stage, having no production before treatment, delivered up to 7000 BOPD after treatment. In these low-permeability assets, the post-fracturing response shows good results in general terms, increasing final conductivity in the near-wellbore area, and improving the production in these wells. The fracture gradient observed varies from 0.715 to 0.981 psi/ft with an average minimum stress of 13,670 psi. To perform the acid fracturing treatments, an average of 6400 hydraulic horsepower (HHP) must be available, with up to 13,400-psi surface pressure observed. As such, a stimulation vessel is necessary in all operations, applying a 26-bbl/min average pumping rate. Globally, acid fracturing treatments are a common stimulation technique. This study shows that stimulating proper candidates in Mexico using acid fracturing significantly helps increase production, which may be relevant for the exploitation of new areas where fracturing has not been implemented.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".