Modelling and analysis of systems on offshore oil and gas platforms

Abstract

This research examines oil and gas systems from the seemingly underutilized perspective of energy; this is counterintuitive since the energy content of hydrocarbon products is its most distinguishing characteristic and the very reason why it is valued by society. It is clear that the amount of energy required to extract crude oil is increasing over time, at the long-term global level, and at the much shorter time span of individual fields. The global trend is a well-documented phenomenon and is related to the depletion of the most energetically favorable reservoirs and a coincidental growing global demand for energy. Concerning existing fields, it is often necessary to implement increasingly higher energy intensity methods to extract the remaining crude oil resources. These trends are the impetus for the industry to gain a better understanding of the relationship between the application of energy and the production of crude oil across a wide spectrum of production methods. Reservoir management and petroleum engineering are highly evolved and scientifically rigorous disciplines, but their practices and methods tend to circumvent the single most important, value-added, quality of hydrocarbon extraction systems, the actual energy recovered, which is the difference between the energy extracted and the energy applied. Therefore, the motivation for this research is to outline existing energy evaluation methods which can be applied to oil extraction systems, illuminate the elements of these methods which can provide the greatest practical advantage to the oil and gas industry, and last, but certainly not least, to demonstrate the pivotal role of energy in crude oil extraction systems. As such, case studies are developed for three small offshore oilfields. The techniques applied include the identification of appropriate boundaries for the system, subsystems and equipment items, the calculation of energy related balances at each level, the development of energy related performance indicators, and lastly, analysis of performance. Indicators, such as the Energy Intensity (EI) and the Energy Return on Investment (EROI), are derived for different levels of the crude oil extraction systems. The dimensionless EROI is the energy returned divided by the energy invested, while the thermodynamic EI is essentially the inverse of the EROI, although alternative dimensional EIs may also be applied on a commodity or process basis. The case studies begin by developing long term time-series EROIs for three oil fields, with breakdowns that take into account the construction, drilling and operational phases of each field. The results corroborated the work of other researchers that indicated that the energy required to produce crude oil at the individual field level increases over time. The calculated EROIs drop steeply in all three fields as the crude oil production declines and the production of associated formation water increases. The increasing energy intensity of the production operations phase tends to dominate the long-term EROI behaviour since construction energy is recovered quickly and drilling energy tends to decrease after the initial wells are drilled. A more focused perspective is applied to address the main energy consumers of the three fields. It is learned that the drivers for energy consumption are the downhole Electrical Submersible Pumps (ESPs) and the surface mounted water disposal, or injection pumps, which together constitute more than 95% of the total energy consumed in each of the three offshore fields. There are relatively few water disposal, or injection, pumps and their performance is well understood. On the other hand, the numerous ESPs, which are narrow multi-staged centrifugal pumps installed downhole in the casing of the well, are more notable due to the extreme conditions in which they operate, the diversity of operating conditions, and their essential role in extracting hydrocarbons from the reservoirs. Consequently, a set of 18 ESPs are analyzed in detail by conducting energy balances around each pump's electrical and hydraulic subsystems. It is shown that the greatest energy losses in the ESP system are the hydraulic losses which occur within the pumps themselves. It is also learned that the performance of the ESPs varies considerably among the population in terms of their energy returns (EROIs), EIs and related fuel costs, and that this information can be used to prioritize and rank the wells. Over the course of this research, it became evident that each energetic indicator serves a very distinct purpose. The EI is a parameter which can be used to better understand the efficiency of processes and products, which is essential information for oil and gas operational managers in terms of pursuing energy optimization, while the EROI parameter is a more holistic indicator which is related to the value of energy derived from a system or subsystem, and how it is affected by different activities and conditions. It is suggested that the EROI indicator can be applied by oil and gas managers to support decision making with respect to fields, platform and to some extent to individual wells. This researcher also believes that the EROI concept can be applied on a strategic level in support of a portfolio level evaluations. Furthermore, this researcher suggests that governmental regulators can potentially use estimated EROIs when developing fiscal terms and conditions for oil and gas concessions. Finally, it should be noted that while ESP equipment items are modestly priced, the cost of installation, or of replacement of failed ESPs, is quite expensive due to the equipment, labor and time required for well interventions. Additionally, the loss of revenue from failed ESPs can be significant. Therefore, the pursuit of high ESP availability rates is a worthwhile goal, and a system that can predict, and potentially prevent, failures would be highly beneficial to oil and gas operators. As such, a fuzzy logical system which utilizes trend pattern matching for operational parameters is developed and tested. A derived first-pass pattern matching system based on fuzzy logic is applied to nine case studies of ESPs. The system is unable to detect an impending failure mode, but is able to distinguish between ESPs experiencing problems and ESPs running smoothly