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Improving production is a main goal in the industry, mainly in countries where now it is possible to apply accessible technology. Digital Oil Field projects have been successfully implemented worldwide, showing their value in terms of losses reduction and oil production optimization. Annular Gas handling system (AGHS) is part of those projects, aiming to improve well production systems. Gas accumulation in the annulus is a well-known operational condition which may lead, depending on the volume and associated gas, to ESP production system issues (gas lock). With this in mind, a technical team was formed to create an autonomous annular gas handling system with the main objective to optimize production by avoiding gas related issues, but also to reduce human intervention in the process. This is translated into less kilometers driven and therefore less people exposure. The main task of the gas handling system consists in regulate the gas outlet through an automatic valve according to a remote order. This order can be given as a percentage of opening denominated "manual control", or as a value of casing head pressure (CHP), denominated "automatic mode" where the valve keeps adjusting automatically in order to maintain the set point pressure (SP). In this way, the manual operation of the annulus valve from an operator on-field is no more needed. This case solution presents the pilot test results and a feasibility analysis for the expansion of the AGHS Skids. The pilot included two wells in the Auca brownfield: ACAK-182 and ACAK-124, in which an incremental production of 30% and 12% respectively was achieved after pilot implementation. Additionally, manual annular valve interventions were reduced 98% after the automated gas-handling system was tested. This project demonstrated that intelligent, customized and specific solutions enabled incremental production at a very low cost, reducing people exposure by avoiding trips from pad to pad for annular valve manipulation. Additionally, AGHS Skid improved the efficiency of the ESP in 11% and reduced energy consumption in 11% KVA resulting in higher production with lower power consumption. Also, people were able to spend time working on production optimization rather than operational tasks. |
