ABSTRACT
The realization that much value can be extracted from the data routinely collected during drilling, completion, stimulation, workover, injection, and production operations in the upstream exploration and production industry has resulted in a growing interest in the application of data-driven analytics in the industry. Petroleum data analytics is the application of data-driven analytics and big data analytics in the upstream oil and gas industry. Data mining and machine learning techniques must be used in order to deduce information and knowledge from the raw data that resides in the databases. Data mining has been able to attract the attention of many in the fields of scientific research, business, the banking sector, intelligence agencies, and many others from the early days of its inception. Data mining is used in the banking sector for credit card fraud detection by identifying the patterns involved in fraudulent transactions. It is also used to reduce credit risk by classifying a potential client and predicting bad loans.
