OIL DEPOSITS IN THE FIELD OF TURKMENISTAN: INDUSTRIAL EVALUATION BY STATISTICAL METHOD
DOI:
https://doi.org/10.4314/njt.v43i4.25Keywords:
Well Flow Rates, Landscape, Monthly Decline Rate, Reservoir, Production DynamicsAbstract
The purpose of this study is to analyse and evalute the effectiveness of the statistical method in estimating oil reserves on the example of a field in Turkmenistan. Various methods such as analytical, statistical, correlation tables, moving average, calculation were used to arrive at the conclusion. Residual oil reserves were estimated taking into account different types of wells and cumulative production, which provided a more complete picture of the field’s potential. The results of the study showed that the use of statistical method for estimating oil reserves in the Goturdepe field in Turkmenistan is of high importance for effective production management. The analysis of well production data and the application of statistical methods allowed the identification of important trends and patterns in oil production, which is a key step for optimizing the field development process. One of the key findings of the study is the need to account not only for current production, but also to forecast future production. This helps to optimize the field development process and make informed decisions about further investment. Within the framework of this study, it was noted that, given the complex geology of the region, the use of statistical methods is critical to ensure the accuracy and reliability of reserve estimates. This approach allows for the consideration of many factors, including variations in production and geological features, providing more accurate estimation results and informed decision-making in the management of oil production in Turkmenistan. The results of the study confirm the effectiveness of the statistical method for estimating oil reserves in the Goturdepe field, which contributes to effective production management and also allows optimization of the field development process, helping to improve the efficiency and reliability of production in the region.
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