Giant, geologically complex heavy oil fields can take decades to develop, so development decisions made early in the life of the field can have long-range implications. Decision and risk analysis (D&RA) is often used to make decisions that will maximize risk-adjusted economic benefit. Unfortunately in large heavy oil fields, D&RA can be very challenging due to the large number of variables and the endless number of development and expansion scenarios to analyze. The time needed to complete a D&RA can become prohibitive when full-field reservoir simulation is the main tool for forecasting primary production and well count, with one simulation taking many hours or days to complete.
This paper describes two new simulation tools developed to overcome these challenges: 1) a method for populating a model with hundreds-to-thousands of horizontal wells, and 2) a method to quickly and directly optimize expansion decisions.
A semi-automated spreadsheet-and-simulation method was developed to quickly place and select hundreds-to-thousands of hypothetical/future horizontal wells in a multi-million grid-block model. Because the method automatically accounted for all model static properties and their effects on dynamic production response, the hypothetical wells had productivity characteristics very similar to actual drilled wells placed in the model.
A multi-variant non-linear interpolation method was developed that enabled full-field forecasts – for any combination of acreage allocation, well count, drilling order, and expansion rate constraint – to be calculated in less than 5 seconds, compared to about 20 hours for traditional simulation. Extensive validation work showed that well count and production curves from the spreadsheet virtually overlaid those obtained using traditional simulation of the particular expansion scenario. Such close agreement was possible because the basis of the spreadsheet forecast was utilization of traditional simulation forecasts from a handful of relevant cases.
A key breakthrough beyond just fast forecasting was the coupling of the following three components inside the same spreadsheet: the fast forecasting method, calculation of an economic indicator/objective function (NPV), and commercial optimization tools. This linkage made possible, perhaps for the first time (at least at this scale), realization of direct optimization of any development scenario in a matter of minutes to a few hours, depending on the number of variables being optimized.