Efficient Water Softening in Heavy Oil Steamflood Operations

Abstract

Pigging of once through steam generators (OTSGs) has indicated various types of scales, the most predominant of these being silicates of hardness causing ions. It was noted that scaling propensity can potentially go up with higher steam quality (SQ) as the reject stream gets concentrated with ions. However, models suggested that there are benefits of higher SQ in enhancing fuel savings (8%) and electricity savings (2%) when SQ was increased by 20%. The challenges of higher SQ were noted in terms of increased scaling tendency and therefore the need for improved softening. In Field D, the service cycle, the backwash cycle, and the brining cycle were optimized leading to a gain in throughput and reduction in salt consumption. Service cycle improvement gained 30 to 130% in throughput between two regenerations, backwash cycle improvement by fluidizing the bed to nearly 35% helped gain 10% in throughput, and reduction of brining cycle from 75 to 48 minutes helped reduce salt consumption by 56% without impacting the throughput. In Field B, a 6-month pilot revealed that shallow shell resins where ion exchange is more efficient due to inert core (better intraparticle diffusion control) can enhance the throughput by 30 to 80% and simultaneously reduce the number of regenerations by 15 to 30%. Resin fouling is still a major challenge to contend with as oil can foul the resin and throughput can decline by 0.5 to 3 folds. In a plant operation, where there are multiple softener and brine vessels, there is a need to optimize them as a system. Reliability, availability, and maintainability (RAM) models are used in Field C to (a) address equipment configuration optimization with impact on capital capacity expansion project scope, (b) understand how net soft water delivery capacity was affected by increases in inlet hardness, and (c) assess through a comparison scenario if the large cost of addressing the valve issue in an upstream nutshell filter was worth the lost production opportunity related to unplanned downtime.