Optimization Algorithm of Hydrogen Sulfide Scavenging Process in Oil Production Industry

Abstract

Hydrogen sulfide (H2S), usually present in oil reservoirs, is a toxic and corrosive gas that may have its origin associated with bacteria's metabolism or thermochemical reactions. This gas which is already present in the atmosphere can be converted into sulfur dioxide (SO2), contributing to the greenhouse effect. In presence of water it forms sulfuric acid and precipitates as acid rain. Given its physicochemical properties, H2S tends to accumulate in spaces with little ventilation; being a serious condition in operational processes. Even in low concentrations it causes health problems, and itis lethal in concentrations close to 700 ppm. Nevertheless, the corrosive potential must also be considered, mainly during production due to the piping can be affected with leaks. Therefore, the treatment should still be effective close to the reservoir during the oil production process. These problems must be overcome by the effective reduction or removal of this gas from the oil stream. The use of H2S scavengers in oil industry is a useful practice in order to remove or reduce gas concentration. Hydrogen sulfide scavengers based on triazines are used, since they are liquid substances that can be used in gas systems, being able to be injected directly into the stream with great mixing capacity. The triazine reacts with H2S producing soluble and inert products, which are collected during production system. In order to monitoring H2S concentration, a software SIMSeq 1.0 was used to simulate operational conditions based on real data from oil wells. Using this software, several simulations were carried out and the optimum injection volume was determined. After the volume set, sensitivities analysis was carried out for different injection depths of scavengers along the well string. The results allowed to draw the best correlation between triazine flowrate and its injection depth. It was done by comparing the scavenger injection depth along the points of injection into wellbore. These results were used to build a predictive model in STATISTICA software with a distribution between volume of injection and sequestration efficiency to support economic feasibility studies for fields and oil wells. Results from this study lead us to believe that for the well studied, considering simulations e statistical analysis performed, the optimum injection depth and flowrate to have H2S concentrations below 5 ppm should be 9500 m for depth and 46 L/h flow rate.