Vazquez, Oscar (Heriot-Watt University) | Ross, Gill (Shell U.K. Ltd) | Jordan, Myles (Nalco-Champion) | Baskoro, Dionysius Angga Adhi (Heriot-Watt University) | Mackay, Eric (Heriot-Watt University) | Johnson, Clare (Nalco-Champion) | Strachan, Alistair (Nalco-Champion)
Oilfield scale deposition is one of the important flow assurance challenges facing the oil industry. There are a number of methods to mitigate oilfield scale such as sulphate reduction of the injected brine, flow modification to reduce water flow, damage removal by dissolvers or physically by milling or reperforating, and finally, inhibition, particularly recommended if a severe risk of sulphate scale deposition is present. Inhibition consists of the injection of a chemical which prevents the deposition of scale, either by stopping nucleation or retarding crystal growth. The inhibiting chemicals are either injected in a dedicated continuous line, or bull-headed as a batch treatment into the formation, commonly known as a scale squeeze treatment. Generally, scale squeeze treatments consists of the following stages: preflush, to condition the formation or act as a buffer to displace tubing fluids; main treatment, where the main pill of chemical is injected; overflush, to displace the chemical deep into the reservoir; followed by a shut-in stage to allow further chemical retention; finally, the well is put back in production. The well will be protected as long as the concentration of chemical in the produced brine is above a certain threshold, commonly known as minimum inhibitor concentration (MIC), usually this value is between 1 and 20 ppm. The most important factor in a squeeze treatment design is the squeeze lifetime, which is determined by the volume of water or days of production where the chemical return concentration is above MIC.
The main purpose of this paper is to describe the automatic optimisation of squeeze treatment designs using an optimisation algorithm, in particular, using particle swarm optimisation (PSO). The algorithm provides the optimum design, which strictly speaking in terms of squeeze treatment designs, it provides the longest squeeze lifetime, although, it might not be the most efficient. To determine the most efficient design, an optimisation algorithm is used to provide an optimum design based on the following objectives: operational deployment costs, chemical cost, total injected water volume and squeeze treatment lifetime. Operational deployment costs include support vessel, pump and tank hire. There might not be a single design optimising all objectives, thus the problem becomes a multi-objective optimisation. The algorithm is capable of analysing a great number of designs, making it easy to identify the designs that are non-dominated, which provides the right amount of information to identify the most cost effective squeeze treatment design, and therefore cutting total treatment costs.