Reservoir Management in Howard-Glasscock Field: Waterflood Redevelopment in a 90 Year Old Field
Bibliographic record
Abstract
Abstract This paper presents the integrated approach for the redevelopment of the waterflood in Howard-Glasscock field located primarily in Howard County, Texas. Originally discovered in 1925, the majority of production is now commingled across the Guadalupe, Glorieta and Clearfork formations. This is a mature field which is currently in the midst of a 5 and 10 acre infill drilling program that began in 2009. Emphasis has primarily been focused on drilling producing wells, but the basis for this project was to optimize an existing waterflood to guide the development strategy of the field moving forward. A study of the production of the wells drilled since 2009 identified stronger performance in wells with offset waterflood support. On average, waterflood was responsible for a 22% improvement in the expected recovery per well, despite a lack of patterns or a comprehensive waterflood management plan. As a result, a multi-disciplined team was commissioned to design a strategy for the redevelopment of the flood and more active management of the daily operations. Geology and reservoir engineering aspects were used to characterize the reservoir in conjunction with classical waterflood methods to understand the current performance and validate the expectations for secondary recovery. Fracture orientation was studied based on cases of early breakthrough and was utilized in pattern identification and well placement to maximize sweep and discourage direct communication between injectors and producers. Further, the success of the waterflood in Howard-Glasscock relies on the ability to control the flow of water over a 2,000 foot vertical interval. To address this, the team has implemented a surveillance plan with improved monitoring and communication with the operations team to enhance the collection of data and in order to react to the dynamics of a waterflood. The rapid response to injection observed in this field requires proper surveillance and timely control of water flow which ultimately drives the success of the program by moving water from high water cut intervals to bypassed oil zones. This paper details the systematic approach that was used to design the redevelopment plan for a waterflood in a 90 year old field. The scope of work is being implemented and represents an adjustment in the development plan of Howard-Glasscock moving forward. Ultimately, the enhanced performance observed in recent drilling programs and the continued success of development in this mature field hinges on understanding and managing the waterflood moving forward.
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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".