Analysis of geothermal casing thinning rate of Leyte geothermal production field

Abstract

Corrosion is one of the technological problems that geothermal management faces in the operation of geothermal wells. The primary cause of corrosion in geothermal wells is exposure to geothermal brine where conductive and convective heat transfer happens from the reservoir to the surface. The geothermal well supplies the motive two-phase steam fluid from the reservoir to the surface fluid collection facility, and then to the separator where steam is separate from brine. The casing of the well is the first equipment that encounters the field’s geothermal fluid. The flow of geothermal brine from the reservoir causes the casing to deteriorate by way of corrosion. The impact of turbulence, corrosion and erosion significantly reduce the integrity of the casing. Thus, monitoring these facilities is vitally important to minimize the risks to geothermal operations. Caliper measurements are taken to monitor the thickness of the casing for safety and environmental concerns.

The effective management of a geothermal well necessitates a very thorough knowledge of the extent to which the aforementioned factors contribute to casing degradation. In this paper, the contribution of factors affecting the thinning rate of a geothermal casing, such as temperature, flow velocity, pH, well geometry and corrosion species, was studied. The effects of several corrosive species on casings were also studied. The corrosive species and the factors affecting the thinning rate of the production wells of the Leyte geothermal production field were analysed with multiple linear regression models in order to determine the dependency of the thinning rate on these parameters. Fluid discharge measurements and sampled chemistry concentrations at the surface were simulated at downhole conditions using software HOLA and WATCH. The results were analysed statistically using ANOVA, a P value test, and multiple regression coefficients. Adjusted R2 of the regression analysis and mean absolute percentage error (MAPE) aided in selecting a good regression model. The study showed that fluid discharge characteristics such as temperature, velocity, pH, steam fraction and geometry of the well contribute about 56.71% to the thinning rate of the casing. The predicted thinning rate model also shows similar trending of the average thinning rate compared to the measured thinning rate for the first and second surveys of repeatedly measured wells.