Identification of Contaminanted Data in Hydraulic Fracturing Databases: Application to the Codell Formation in the DJ Basin

With the advance of computer technologies, digitized data is becoming increasingly available. Currently, many companies are in possession of oil or gas-field databases that contain large amounts of information related to hydraulic fracturing, reservoir characterization, production, drilling, etc. However, not all the records are completely accurate or reflect reality. Errors in stored data can be subjective or objective and can be the result of improper or incomplete data collection, errors in data entry, lack of proper interpretation and others. These errors can later lead to poor, erroneous, or even impossible interpretation of the data. This leads to the question: how much of the data is reliable and how can the contaminated data be identified?