Generating revenue from non-profitable targets. Successful Implementation of HiWAY & TSO fracture techniques in Shushufindi Field
Bibliographic record
Abstract
The giant Shushufindi field, discovered in 1968, is located in the North-East of the Orient basin in Ecuador, neighboring Maranon and Putumayo basins in Peru and Colombia, respectively. The field belongs to Block 57, it started production in 1972 and is sparsely developed with 165 active wells. The production comes from two of the main cretaceous reservoirs: Ti and Ui, with Ts, Us and BT as secondary targets. The challenge to obtain incremental production from the main reservoirs becomes a tough task. The emphasis on producing from the secondary reservoirs turns into a crucial target for meeting the production expectations in the low production or abandoned wells. The main challenges in the secondary reservoirs are intermediate petrophysical properties, stratigraphic variability, low pay, lateral discontinuity, and shale intercalations. However, there is an important volume of recoverable volumes associated in these sands that makes them an attractive target for production enhancement. Performing conventional operation in secondary reservoirs has a wide margin of risk in terms of incremental production, where the average oil production is ~120 BOPD. A strategy to improve conductivity in these marginal reservoirs is hydraulic fracturing. Induced fractures enhance permeability greatly by connecting pores together; with this, hydraulic fracturing becomes a critical technology to increase production. The effectiveness of hydraulic fracturing is determined by the propped conductivity and geometry,the fracture height, and half-length. Pad volume and proppant concentration also play an important role in the fracture-treatment design because they determine final propped fracture penetration and conductivity. A good understanding of the reservoir characteristics, together with a fit-to-purpose fracture design, led to a successful implementation of TSO and HiWAY fracture designs in the Shushufindi field, with outstanding results. During the 2018-2019 WO campaign, nine (9) well interventions involved hydraulic fracturing in secondary targets and two (2) in main targets. The execution of these jobs exceeded expectations generating oil production of 7000 BOPD (790 BOPD/well) after the jobs and revenue to the project, which translates to an estimated 6.9MM Bbls of recoverable reserves.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".