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Oil Sands Plant Infrastructure

Opgrade Study Establishes Business Case for $700 mil Infrastructure Investment


Opgrade Plant Performance Study

50 Words or Less

By utilizing our proprietary reliability-based capital investment decision tool, our client can proceed with confidence knowing that their $700 million capital improvement project will generate ample return on investment. The study also identified $30 million in possible revenue improvements and at least $40 million in possible capital expenditure reductions.

Opgrade’s Performance Study identified $70 million in revenue enhancements and capital expenditure reductions for this Alberta plant.

Project Background

Our client, a Canadian-based energy company, has a facility in Alberta to recover and upgrade oil-sands (bitumen) reserves. Their existing facility includes a Steam-Assisted Gravity Drainage (SAGD) plant that recovers bitumen by injecting steam into the ground, and an Upgrader Plant that transforms the recovered bitumen into a Premium Synthetic Crude, which is then pumped to a pipeline for sale at roughly the WTI (West Texas Intermediate) spot price for crude

To maximize production (and therefore profits) the Upgrader plant needs a consistent and continuous input stream of diluted bitumen from the SAGD plant. Our client’s existing SAGD plant was not producing its expected flow of bitumen and consequently they began looking at options to add another SAGD production facility.

Every plant experiences both unplanned and planned maintenance outages. Supply, intermediate and product tanks can mitigate the effect of these outages when they occur. Therefore our client also wished to evaluate the addition of several tanks.

Study Objectives

As with all studies we perform of this nature, the goal of this study was to scientifically calculate how capital investment decisions affect revenue when taking plant reliability into account. Specifically, the objectives were:

  1. Build a model with a second SAGD facility and calculate the improvement in the on-stream factors for the various product streams

  2. For each of the proposed new tanks, calculate the tank size that maximizes return on investment.

A New Kind of Modeling Tool

There are many reliability simulation tools available, but few incorporate tanks and none calculate flows with dynamic mass balances and actual operational rules. Therefore a new kind of modeling tool was necessary to calculate the results our client wanted.

Our Opgrade Plant Performance tool fuses the best features of other limited tools into one comprehensive package. Opgrade was designed from the ground-up specifically to predict a plant’s future revenues with a reliability flow solver that calculates expected production based on a plant’s actual equipment configurations, reliability data, mass balances, operational rules, and tank logic.

Process Inputs & Outputs

Inputs to this process include the recovered bitumen from the field, diluent to dilute the bitumen (so it can flow in a pipeline), make-up water for steam production, and a small stream of bitumen imported from a third party.

There are several products associated with this process. The primary product, for obvious reasons, is the Premium Synthetic Crude. Secondary products include diluted bitumen from the SAGD plant and the “cracked” diluted bitumen (which contains olefins and therefore sells for a lower price). Butane is also produced, but it is normally blended into the primary product stream. Waste streams include sulfur and an ash slurry.

Failure Data

With all reliability-based studies, good failure data is fundamental to providing meaningful results. As the adage goes, garbage in: garbage out. For all O studies, we use a combination of trusted failure data sources from industry and vendor databases. All data undergoes a thorough vetting process with the project team before it is used in any study.

Objective 1 Results

After carefully studying and validating this system, the additional capital is predicted to improve revenue by 14.9%

Table 1 – Objective 1 Results

Figure 1 – Block Flow Diagram of the facility with infrastructure improvement options

Modeling the Existing Plant

Modeling the existing plant was a necessary step for two important reasons:

  1. The existing plant model establishes the baseline for evaluating any possible production improvements.

  2. Results from existing facility model were validated by matching them with operational history. This proves the methodology is sound.

Additional Infrastructure

The additional capital infrastructure was modeled in the same manner as the existing plant, including a second SAGD facility, new supply and product tanks, larger intermediate tanks, and new interconnects (see Figure 1).

Objective 2 Results

To evaluate the proposed tank sizes, sensitivity case models were run that varied the sizes of each tank, one at a time. As illustrated in the chart below, several tank sizes can be reduced without harming production. This yielded capital savings of at least $40 million.

Chart 1 – Objective 2 Results Sample

Other Sensitivity Cases

Realizing the power and benefit of the model, our client asked that we build several other sensitivity case models to evaluate other potential investments. One such case was to add additional capacity to produce hydrogen (a necessary component for hydrocracking, a part of the crude upgrading process).

The additional hydrogen supply improves the on-stream factor by 1.5%, yielding a possible annual revenue improvement of about $30 million.

Maximize Return on Investment

At the end of the study, our client was able to move forward confidently knowing that the infrastructure improvements they were evaluating would generate sufficient return on investment to justify the Capital Expenditure (CapEx). In fact, assuming a WTI equivalent spot price of $100, per barrel, this Opgrade study shows the infrastructure improvements generate a return on investment (IRR) in excess of 30%.

Beyond the CapEx justification, this study also demonstrated the possibility of at least $40 million in CapEx reductions and $30 million in annual revenue improvements. When compared to the cost of the study, either outcome generates a return of 100:1 in the first year.

Learn More

To learn more about Opgrade studies contact our team today!

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