Equipment sizing decisions in the Oil and Gas Industry often have to be made based on incomplete data. Often, the exact process conditions are based on numerous assumptions about well performance, market conditions, environmental conditions and others. Since the ultimate goal is to meet production commitments, the traditional way of addressing this is, to use worst case conditions, and often adding margins onto these. This will invariably lead to plants that are oversized, in some instances by large margins.
In reality, the operating conditions are very rarely the assumed worst case conditions, but they are usually more benign most of the time. Plants designed based on worst case conditions, once in operation, will therefore usually not operate under optimum conditions, have reduced flexibility, and therefore cause both higher capital expenses and operating expenses. The use of statistical and probabilistic tools allows to better account for the unpredictability of component performance, as well as for ambient conditions and demand. This can help design plants that perform best under the most likely scenarios, as opposed to traditional designs that tend to work best under unlikely worst case scenarios.
During Front End Engineering Design (FEED) Process engineers often make blanket assumptions on pressure losses across process exchangers, vessels, control valves, etc. which can vary significantly from individual losses as defined in the manufacturer’s specifications. Certain license processes will also recommend that a + 10% margin on flow be added to accommodate uncertainty during operation. These have been found to result in vast discrepancies between what was specified in a design office and what is found during start up in the field. Due to uncertainties in the actual design conditions for most oil and gas compression applications, compression units often are needlessly oversized. Therefore they are more expensive, and generate higher operating expenses than units that are sized closer to the actual operating conditions.
The argument for oversizing is often, that these oversized units will always provide enough power to meet the operating conditions under any circumstances. However, the probability that all difficult circumstances occur at the same time is very small. All too often , these margins are applied, while looking at the equipment performance under the most extreme conditions, that is, the compressor at its highest power operating point, and the gas turbine at the highest possible ambient temperature.
Needless to say that, even without the margin, the probability that the gas turbine can ever use its maximum power is virtually nil. Rather, the units, including the process valves, and process separators are oversized for practical operation purposes. Operating oversized equipment is usually a challenge: Valves tend to have poor controllability, and separators may operate at low separation efficiency if the flow they actually have to handle is much smaller than what they were designed for. Compressors may run in recycle, or very close to the control line. Despite expensive company specifications and upper quartile maintenance practices, off design operation continues to plague the industry with catastrophic failures and inefficient plant operation.
Recent data taken from 1 major Petrochemical producer indicated that over 80% of the pumps surveyed operated away from their intended design point by up to 20%. One estimate, places this cost at over 5 billion dollars per year to the global energy and petrochemical industries largely stemming from failure and operational inefficiency .
The Monte Carlo analysis approach has been widely applied in Risk Assessment. It also has been broadly applied for logistical modeling of process plants, working on gross plant building blocks. On a smaller scale, the methodology has been applied to electrical systems, including reliability data on individual sensors of electrical components.
