Application of ScaleSoftPitzer in Big Data Era: Evaluations of Water Source, Scale, and Corrosion Risk A Permian Basin study

Application of ScaleSoftPitzer in Big Data Era: Evaluations of Water Source, Scale, and Corrosion Risk A Permian Basin study

Risk assessment

Carbon dioxide

Big data

Corrosion rate

Gas industry

Corrosive effects

Produced Water

Calcite

Database systems

Gypsum

Oil and gas industry would generate a large volume of produced water during the exploration and production. The geochemistry of the produced water can provide valuable information for the analysis of formation water source evolution and the scale and corrosion risk of the production. In past decades, the water sample and the correlated condition have been collected during the production, which accumulate extensive amount of data. The successful analysis of such database would be very helpful for the scale and corrosion management. In this study, the ScaleSoftPitzer (SSP) software is used to proceed the analysis of produced water evolution and scale and corrosion risk. A Permian Basin example is selected based on USGS produced water database V2.3. The formation information from the database was critically reviewed, cleaned and standardized into 13 major formation groups related to the oil and gas production area. The missing depth, temperature and pressure were calculated, and the CO2% and downhole pH were calculated by assuming the downhole brine was in equilibrium with calcite. The saturation indices of various scale are calculated and statistically analyzed. According to our analyzing result, it is found that usually the saturation index of gypsum and barite are close to zero, which suggest that the produced water is in equilibrium with barite and gypsum mineral in the formation. The calculated calcite scale SI are generally larger than 1.0, suggested potential calcite scale risk. 1 mg/L of NTMP is recommended for all Permian Basin well for preventive scale control. The CO2 corrosion risk was also calculated using the corrosion model in SSP, a preventive action is suggested for Permian Basin. Furthermore, a good agreement between the calculated corrosion rate and the measured Mn2+ concentration is observed. This study provided a template to use the produced water database to improve the scale and corrosion management at the field level in this big-data era. Copyright 2022, Society of Petroleum Engineers DOI 10.2118/209519-MS

Wang, Xin

Dai, Zhaoyi Joey

Li, Wei

Ko, Saebom

Paudyal, Samridhdi

Yao, Xuanzhu

Leschied, Cianna

Roy Shen, Yu-Yi

Pimentel, Daniel

Kan, Amy

Tomson, Mason

2022 SPE International Oilfield Scale Conference and Exhibition, OSS 2022, May 25, 2022 - May 26, 2022

2022

conferencePaper

10.2118/209519-MS