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Production availability and capacities

Integrating flow modelling with RAM analysis helps to generate key insights into production issues that cannot be solved by generic RAM approaches alone.

Generic RAM analysis focusses on estimating the time which a system is available – the uptime of the system or its availability. For the oil and gas industry, this is not enough. By adding a flow network and integrating production rates to the system, the methodology can account for degraded states, spare capacities and typical operations such as logistics operations, boosting mechanism and flaring operations and help assess the impact on production over time. What this means is that “actual production” figures can be estimated with greater accuracy. This also results in better projections of production availability over the lifecycle of the facility.

Rather than just providing rudimentary uptime vs. downtime information, production availability keeps track of how much production is lost throughout the system life, and quantifies the efficiency by dividing the actual production by the potential production. Combined with time varying flow from multiple sources, this result becomes a very powerful metric.

Typical oil production profile

Typical oil production profile

For example, consider an oil field that starts its life producing 100 bbls per day and on the second year there is a flow reduction to 50 bbls per day.

Oil production profile for year 1 and 2

Oil production profile for year 1 and 2

This flow reduction is natural. Production from most oil fields begins to decline within a few years of production – a process that starts as a result of pressure reduction and reserve depletion. During the early years of an oil basin, discovery of new reserves which might be phased in can compensate for decline and production may even grow. However, this is typically a short term boost and in the long run, production decline will inevitable occur.

Back to our example, this oil field is connected to a platform – for simplicity we will be considering only one system in the platform, a simple oil export system which has two redundant pumps. Each pump can handle 50% of the flow.

In order avoid  bottlenecks in the system, these pumps are designed to handle the peak capacity of the oil flowing through the platform– in this case, 100 bbls per day – in the first year. So handling 50% of flow means that each pump should handle at least 50 bbls. This design is fixed – we have to buy a pump that handles at least 50 bbls.

Check the schematic below:

Schematic of an oil export system with 2x50% configuration

Schematic of an oil export system with 2×50% configuration

Now let’s consider that one of pumps has a failure in the first year – this means that the system loses the ability of producing at full capacity – we have two pumps with a combined capacity of exporting 100 bbls and losing one means that we are losing 50 bbls. So the export capacity will be 50 bbls per day:

Schematic of an oil export system with failures on the first year of operations

Schematic of an oil export system with failures on the first year of operations

Moving to the next year, Year 2, let’s assume a failure has happened to the same pump. Now, we have two pumps with a combined capacity of exporting 100 bbls and losing one means that we are losing 50 bbls BUT all we need to export is 50 bbls per day. So the export capacity will be 50 bbls per day – which represents full capacity.

Schematic of an oil export system with failures on the second year of operations

Schematic of an oil export system with failures on the second year of operations

The same approach can be scaled up to reflect the various elements of the processing unit as well as various streams (e.g. oil, gas and water).

This capability allows the analyst to capture in great detail the relationship between design capacities and impact of system availability (specific and combined) on production profile.  Additionally, the increased accuracy to represent all this allows the analyst to predict some extra “production”. This might represent millions of dollars in added revenue throughout the life of an oil field. Better modelling capabilities normally represents better decision-making process.

Such information is central to making robust decisions and effective planning over the lifecycle of the field. For example, when interventions are needed to improve production? Or when capacity changes need to implemented to maximize the use of available infrastructure e.g. cargo ships? Such insights are key to effective decision making. Their value, rather ironically, cannot be quantified.

This is only one of the benefits of combining flow modelling to RAM analysis. The methodology can be extended to include flaring and export operations, boosting mechanism and so on.

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