Buoyancy-Enhanced Membrane Filtration for Oilfield Produced Water Recycle and Reuse
Bibliographic record
Abstract
Abstract Membranes have been used in water treatment for decades and are highly effective industrial wastewater treatment solutions. Despite being a trusted form of filtration, membrane treatment is characterized by high energy consumption, membrane fouling, and excessive maintenance requirements that make membrane treatment systems expensive to own and operate. The high tendency for fouling has also restricted the application of membranes in industrial wastewaters and oilfield produced waters that typically have a significant presence of both solids, oil and grease. A proprietary process known as buoyancy-enhanced membrane filtration ("BEMF") has been developed to drastically decrease the energy consumption, fouling, and maintenance of conventional polymeric tubular membranes in difficult wastewater applications. The hydraulic manipulations implemented in the BEMF process also enable the conventional membranes to operate at 3x–6x the flux rates of a conventional process design, thus reducing equipment size requirements for most applications. This BEMF process achieves increased flux rates with decreased energy, fouling, and maintenance costs by applying a proprietary two-step hydraulic manipulation of produced water within the system. First, the injection of air creates bubble attachment to oils, solids, and other contaminants in the incoming produced water stream. Second, a spiral flow pattern is induced to develop buoyancy-based separation of the water and contaminants. An annular flow is created throughout the entire length of the membranes, with centrifugal forces generating the highest liquid velocities at the surface of the membrane and the contaminants/gas concentrated at the center of the membrane tubes. BEMF has been implemented in multiple heavy industrial wastewater applications and has exhibited a high permeate flux performance in filtering these wastewaters for reuse. The BEMF process is being used by oil and gas companies to recycle and reuse oilfield produced water in their operations to reduce the use of freshwater sources and minimize the trucking of produced water for disposal. A 20,000 bbl/day produced water BEMF system has been deployed for a leading oil and gas producer in the Montney region of British Columbia, Canada, and this BEMF system is the largest produced water ultrafiltration system in Canada. The 20,000 BWPD system was commissioned in July 2023, and the data from the operation and filtration of this oilfield produced water will be included in this presentation. The equipment process and mechanical design, the application details, and the operational data collected up to date will be presented as a technical case study of this first-of-its-kind membrane ultrafiltration system. This system has been installed to recycle produced and flowback water for hydraulic fracturing in unconventional oil and gas wells. The oil company chose to install the BEMFtechnology because of the system’s ability to consistently remove oil, solids, and bacteria while maximizing membrane flux rates, minimizing footprint/electricity, and minimizing the potential for effluent quality upsets. The reduction of harmful bacteria also results in significant downstream savings on biocide, and the increased reuse of produced water for completions will minimize the oil and gas company’s requirements for freshwater sources.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".