Application of Closed Loop Control Logic to Optimise End-of-life Cycling Production in a Mature Gas Field

摘要

The Moomba North gas field is situated in the Cooper Basin in central Australia. Production commenced in 1969 and as the field has matured, liquid loading of wells has become more prevalent. In order to maximise recovery from wells nearing end of life whilst minimising the cost of deliquification methods, a well cycling technique has been implemented. Alternating pressure build-up periods with subsequent flowing periods of flush production allows increased bottom hole flowing pressure to sweep liquids accumulated in the well bore. Parameters dictating desired build up pressure and low-flow shut-in rate have traditionally been calculated and/or determined empirically, requiring regular monitoring and updating to maintain optimal flow rates in line with changing system conditions. Improvements to this methodology have been achieved through implementation of an ‘intelligent’ closed loop control logic code which iteratively monitors and adjusts set points based on historic well performance. This represents an application of technology which mimics engineering input without the need for human intervention. Trial operation on several wells has exhibited the ability of the code to respond to field conditions and operational issues – in some cases increased average flow rate has been observed when compared with parameters manually determined by field engineers. This paper will outline the well control philosophy and development of the control logic. System implementation and additional logic built in to address irregular system conditions and equipment faults will also be included along with field data from trial results. The implementation of closed loop control logic for well control has exhibited improved business outcomes via collaboration between production engineering, process and control engineers and informa- tion technology. The use of an automated closed loop system for mature field well control represents progress in intelligent field control in Australia and provides potential for adaptation to further applica- tions in multi-well control.