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    Evaluation of the production potential of Shilaif shale oil formation using analytical and modeling methods

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    Author
    Alzaabi, Mohamed A.
    Advisor
    Ozkan, E.
    Date issued
    2017
    Keywords
    evaluation
    shale
    unconventional
    modeling
    analytical
    tight
    
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    URI
    https://hdl.handle.net/11124/172134
    Abstract
    In the early 2000s, the oil and gas industry witnessed a boom of hydrocarbon production from unconventional reservoirs. In 2015, about half of the United States oil production came from unconventional reservoirs (EIA 2017). Unconventional oil reservoirs include, but are not limited to, shale oil reservoirs that are usually the source formations for oil trapped in conventional reservoirs. Due to the huge success of shale oil reservoir development in the US, many other countries around the world, especially countries rich in conventional oil, are currently investigating their unconventional reservoir potential in order to increase their production capabilities to match the world’s ever-increasing demand for oil. Realizing that the importance and contribution of unconventional production to the energy sufficiency in the United States might lead to a similar interest in the UAE in the near future, my research is based on a numerical modeling study using data from a single exploration well in a UAE unconventional shale oil reservoir, namely Shilaif. In addition to modeling, the study includes valuable well test analysis results which helped in assessing reservoir properties. The results of the study indicate that Shilaif has favorable characteristics to be a potential target for shale oil production. However, due to the limited amount of information, data quality, and potential bias in selecting samples, interpreting measurements, and analyzing results, this conclusion should be taken as a preliminary assessment and verified with further data and analysis. One of the most important sources of information to guide future assessments is reliable production and flowback. More core sampling and log-core correlations may also improve the level of confidence in future studies.
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