Workover Rig Scheduling Using Reservoir Simulation

Abstract

In this paper we will discuss the results of a prototype software application to view the rig schedule generated by a reservoir simulator. Visualization of simulation rig schedules and comparing with planned rig schedule would help in identifying opportunities to improve operations. With the help of the schedule chart and rig movement data, we better the schedule generated by trying to reduce the net distance traveled by the rig and reduce the number of rigs utilized. We ensure that the overall field oil production is not affected for all the cases.Using reservoir simulation as a tool to assist in the rig planning and scheduling process has the potential to foster team collaboration between reservoir engineering, planning and operations team and facilitate better Integrated field management. The teams would appreciate the challenges associated with planning and scheduling activities for the field.

A data-driven optimization model for the workover rig scheduling problem: Case study in an oil company

“…A few other variations of the WRSP can be found in the literature. For instance, Lasrado (2008) developed a software application using manual procedures combined with reservoir simulation (de Andrade Filho, 1994) to create schedules minimizing the number of rigs and the traveling distances, which reduces contract and transportation costs. Marques et al (2014) proposed a decision support system that schedules a homogeneous fleet of offshore rigs aiming to minimize its size and utilization through MILP.…”

Mathematical Programming Models and Local Search Algorithms for the Offshore Rig Scheduling Problem

“…Also in that year, Lasrado (2008) developed an application and a methodology for the workover rig scheduling problem using an adaptation of the reservoir simulation technique proposed years before by de Andrade Filho (1994).…”

Data-Driven Joint Chance-Constrained Optimization for the Workover Rig Scheduling Problem

“…A few variations of the WRSP can be found in the literature. Specifically, Lasrado (2008) created an application based on a manual methodology that adapted the reservoir simulation technique from de Andrade Filho (1994) to generate schedules and minimize the number of rigs and traveling distances, reducing transportation and contract costs. Marques et al (2014) presented a decision support system that uses a MILP model to size and schedule homogeneous offshore rigs, minimizing the fleet size and maximizing its utilization.…”

“…The most common approach in the RSP to assess the impact of uncertainties is through simulation models. de Andrade Filho (1994), Cong et al (2008), Lasrado (2008), Litvak et al (2011) used reservoir simulation tools to model the uncertainty associated with the reservoir, Gutleber et al (1995) simulated the oil production for a given rig fleet availability, and Zahran and Al-Fardan (2014) used simulation to assemble scenarios for a rig scheduling system.…”