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"Kills 99.9% of bacteria". Sounds impressive. Consumers will have seen this claim on supermarket shelves on all kinds of household biocide chemicals such as hand soaps and detergents. In reality, what does this actually mean? Is a kill target of 99.9% an effective biocide? On the face of it, it sounds very good. However, when referring to microbiological populations, like bacteria, this requires context. What was the original number that was reduced by 99.9%? When quantifying microbiological populations, it is common to use extremely large numbers, referenced in logarithms (1.0 × 105 or 1.0 × 106 cells). Reducing bacterial populations by 100% using batch dosed biocide chemicals is an impossible feat. It will never be possible to entirely eliminate 100% of bacterial populations, as some will always survive and potentially recover to pre-dose populations. Therefore, selection of the most efficient biocide chemical is of the utmost importance. In the example scenario of a hand soap, the target of 99.9% is very difficult to achieve. The biocide chemical is applied to the target surface area (hand) and almost immediately diluted and washed off by a running stream of water. The chemical might get a contact time of up to 1 minute to kill 99.9% of bacteria under normal circumstances. Although hand soap is not directly related to control of bacterial populations in oilfield process systems, the theories behind the testing of all biocide chemicals are the same. It boils down to three parameters that need to be tested; chemical, concentration and contact time, tested against microbiological populations. The questions any operator should ask before using a biocide chemical should be; Which biocide chemical?What concentration should be applied?How long should the biocide chemical be added for? By answering these questions, the operator will have learned key points as to the efficiency of the biocide chemicals under test in relation to the required conditions. This paper will discuss a recent example of a biocide chemical evaluation carried out by a Malaysian operator, in which fourteen different biocide chemicals were tested to determine the most efficient biocide chemical. Each biocide chemical was tested under controlled laboratory conditions against both planktonic and sessile mixed microbial consortia populations, and ranked for efficacy.
"Kills 99.9% of bacteria". Sounds impressive. Consumers will have seen this claim on supermarket shelves on all kinds of household biocide chemicals such as hand soaps and detergents. In reality, what does this actually mean? Is a kill target of 99.9% an effective biocide? On the face of it, it sounds very good. However, when referring to microbiological populations, like bacteria, this requires context. What was the original number that was reduced by 99.9%? When quantifying microbiological populations, it is common to use extremely large numbers, referenced in logarithms (1.0 × 105 or 1.0 × 106 cells). Reducing bacterial populations by 100% using batch dosed biocide chemicals is an impossible feat. It will never be possible to entirely eliminate 100% of bacterial populations, as some will always survive and potentially recover to pre-dose populations. Therefore, selection of the most efficient biocide chemical is of the utmost importance. In the example scenario of a hand soap, the target of 99.9% is very difficult to achieve. The biocide chemical is applied to the target surface area (hand) and almost immediately diluted and washed off by a running stream of water. The chemical might get a contact time of up to 1 minute to kill 99.9% of bacteria under normal circumstances. Although hand soap is not directly related to control of bacterial populations in oilfield process systems, the theories behind the testing of all biocide chemicals are the same. It boils down to three parameters that need to be tested; chemical, concentration and contact time, tested against microbiological populations. The questions any operator should ask before using a biocide chemical should be; Which biocide chemical?What concentration should be applied?How long should the biocide chemical be added for? By answering these questions, the operator will have learned key points as to the efficiency of the biocide chemicals under test in relation to the required conditions. This paper will discuss a recent example of a biocide chemical evaluation carried out by a Malaysian operator, in which fourteen different biocide chemicals were tested to determine the most efficient biocide chemical. Each biocide chemical was tested under controlled laboratory conditions against both planktonic and sessile mixed microbial consortia populations, and ranked for efficacy.
Maximizing the recovery factor achieved through water flooding depends on acquiring a detailed understanding of the vertical and areal sweep efficiency. DNA diagnostics can monitor changes in oil contributions from multiple zones and from injectors, becoming a leading indicator for the potential of water breakthrough, loss of injectivity, and the overall advancement of the water front when combined with subsurface information. This allows for proactive management of injection rates and timing to maximize recovery rates for green fields and brownfields alike. DNA diagnostics use DNA markers acquired from microbes. DNA markers of produced fluids are compared to the DNA markers of injected fluids to establish relationships and shared fluid flow. This paper will cover the end to end workflow for long term waterflood monitoring:Establishing end members, even for a mature field, with the use of new samples from offset wells, properly stored samples from existing wells, and the analysis of commingled samples in combination with the subsurface model.Establishing the level of similarity between injectors and producers as an indication for the progression of the waterflood front using methods including Principal Coordinate Analysis (PCoA) of DNA marker profiles.Performing time series analysis and establishing sampling periodicity for effective waterflood monitoring. A pilot project, consisting of 12 producers and 3 injectors in a conventional California reservoir, was conducted to prove the concepts and further develop the required analysis for waterflood monitoring. Fluid samples were taken weekly on each well over 3 weeks to establish the difference in DNA markers between the fluids. The DNA markers were used to determine the probability that injection fluid was being produced from the surrounding wells. These results were overlaid to temporal changes in the Total Fluid Logs. Taken together, the results correlated and confirmed previous water breakthrough information and provided insights into arial and vertical conformance changes. Additionally, the project provided new insights into strength of producer and injector connection based on geological features and with that informing future infill drilling decisions. Waterflood monitoring is a powerful application for DNA diagnostics that is deployable on new and existing waterfloods. The spatial and temporal monitoring limitations of modeling or tracer studies can be improved upon through this non-invasive diagnostic. Initial results demonstrate the insights that can be provided not just for monitoring the waterflood but also for further field development decisions.
The paper discusses on reservoir souring study in a deep water subsea green field as a result of seawater injection. The objectives are to determine likelihood, timing of reservoir souring to happen and amount of expected produced H2S. Offshore deep water development involves considerable CAPEX investment hence reservoir souring requires to be assessed in order to make techno-commercial judgement involving formulating the field development plan, upfront identification of prevention & mitigation strategy, operating strategy and project economics. The study started by performing data gathering involving among others field information, PVT, mineralogy, water analysis data, and production and injection profile. Subsequently, 2D reservoir modelling and 3D reservoir modelling was built. Sensitivities cases were run by varying the injection rate, nutrient loading, rock abstraction capacity, sulphate content, injection temperature and bacteria growth time. This is followed by sensitivity analyses for mitigation options using biocide injection, nitrate injection, H2S scavenging and sulphate removal in the field. Based on the results obtained, prevention and mitigation strategy has been evaluated and ranked followed by comparison with nearby analogue fields. The modelling results of all scenarios indicate that reservoir souring will happen in the field and beyond HSE safety limit. For some scenarios, the H2S partial pressure exceeds NACE limit before end of field life, hence requiring team to re-evaluate material selection options. Water injection rate and rock abstraction capacity have the largest impact to the H2S breakthrough time. Sensitivity analyses for mitigation options have been conducted based on consideration of having options of biocide injection, nitrate injection, H2S scavenging and sulphate removal in the field. Biocide injection does not have considerable effects on H2S level. Nitrate injection only partially reduces H2S generation mainly due to high nutrient content in the reservoir and high sulphate content in the injected seawater. On the other hand, sulphate removal analyses indicate its effectiveness in preventing reservoir from becoming sour. The outcome of the study is then incorporated in the field development plan and operating strategy. The paper highlighted comprehensive step by step approach to understand reservoir souring potential in a deep water development via 2D and 3D modelling approach. This can be included as an important procedure in field development especially involving high CAPEX development whereby critical decision making need to be made upfront. In addition, benchmarking, and learnings from nearby deep water fields help to identify best preventive and remedial option for reservoir souring.
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