ArrowHead Solutions – Probabilistic Resource Cost Quantification

ArrowHead Solution Helps Clients Understand Exploration Opportunities and Competition with First Ever Comprehensive Geological Resource Analysis Coupled with Costs

The Problem

Oil produced from low-permeability reservoirs such as the Bakken and Three Forks Formations in North Dakota and Montana, the Eagle Ford formation in Texas, and the Monterey diatomites in California provides a large marginal source of supply that is already changing the energy outlook in the United States and the world. As economists know, the marginal source of supply sets the price, and thus it is absolutely crucial to understand the cost and volume of the marginal source. Production of such “unconventional” resources is shifting global supply and petroleum pricing and will continue to do so in the future.

Future petroleum production will be influenced greatly by the degree to which United States and worldwide production of accumulations of “light tight oil” can be developed, expanded, and maintained. Over the last several years production has increased rapidly in certain parts of the United States. Projecting future impact requires a careful understanding of not only the quantities but also the associated costs of light tight oil available for future production, i.e., a “resource cost curve” that is accurate, credible, and descriptive of both the resources and their production costs. This understanding is essential in order to evaluate:

1. What other (competing) producers and regions are likely to do
2. Where, what, and when are the best opportunities for you
3. Whether present and future crude prices are likely to be soft or firm

The Need

Oil and gas companies (IOCs, NOCs, and independents), governments, and other investors are striving to understand the impact of unconventional oil (as well as conventional oil and gas and unconventional gas) on prices, quantities, and reserve additions. Prior to this solution, all that has been available are widely varying estimates about in-place volumes put forth by “experts” with varying levels of understanding about the critical variables (geology, cost, reservoir parameters, and production costs). Such volumetric estimates are simply not sufficient to address the foregoing questions. Before this solution, unconventional resources typically have been characterized in terms of large deterministic estimates of original oil in place coupled with projected high well counts and optimistic estimates of ultimate per well production volumes based on initial production rates in selected wells. The belief that large in-place volumes from homogeneous reservoirs (viewed as “containers”) coupled with massive drilling equals a high oil flow rate and therefore soft prices has led to widespread misconception and consequent complacency about the resource base—a pervasive bias toward soon-to-be-low prices and an erroneous belief that resources of light tight oil are available in virtually limitless quantities at prevailing costs. It has led to optimistic estimates of production, export, and potential for energy independence. Policy makers have embraced this view, arguing there is “no problem” because of the surfeit of supply. Such perspective, while widely held, is not correct.

In contrast to this prevalent view, the unconventional resources representing the potential marginal supply of the future, in fact, display a wide range of geological characteristics, well performance, and economic disparity. The resource base and production costs are anything but homogeneous. In reality, cost and rates of production, and therefore the economic competitiveness of various sources, are destined to vary significantly from basin to basin, play to play, and even assessment unit (AU) to assessment unit. You cannot address the foregoing policies and decisions without knowing the explicit costs and geological characteristics of these resources, which will be provided with this solution for the first time.

Examples

As an example, a recent USGS study done in collaboration with various industry operators (meaning it had substantial industry input related to geology and resources) estimated between 4.4 to 11.4 billion barrels of undiscovered and undeveloped technically recoverable oil in Bakken and Three Forks reservoirs, assuming application of current best practice technology. This potential is distributed among six geographically defined areas (assessment units or AUs) in Montana and North Dakota. The estimated mean ultimate recovery per well (EUR) is different for each AU, ranging from 431 thousand barrels/well in sweet spots of the Eastern Transitional Continuous Oil AU to 55 thousand barrels/well in non-sweet spots of the Northwest Transitional Continuous Oil AU. This can hardly be considered a homogeneous, constant-cost resource base. This can hardly be considered a flat supply curve as far as the eye can see. Quite the contrary, it is a supply curve with significant “shape” to it.

Such findings indicate that, although recoverable resources in Bakken and Three Forks reservoirs are indeed extremely large, quality and exploration and production (E&P) costs vary widely across the resource base. The large resource is clearly not all available at today’s production cost. Analyses that treat this resource as a single, huge tranche are flawed and misleading. Not only that, the recoverable volumes themselves are highly uncertain and will only be available at a wide range of costs, from less than $30 to $130/barrel or even higher, assuming current well costs.

As another example, two EIA reports estimated that low permeability reservoirs of the “Monterey Shale” contain 15.4 and 13.7 billion barrels of technically recoverable oil, respectively. No cost was associated, merely a “vat” of oil of that magnitude there for the taking. However, a recent revision from EIA decreased the initial estimates to 600 million barrels of recoverable oil in the same “Monterey Shale.” According to this revision, the “vat” is practically empty! None of these estimates has intrinsic economic or decision-making value. This solution circumvents that.

These solutions avoid the mistake of assuming that the entire volume of a play will be available at a single low cost, or worse, making arbitrary guesses about how the resource might be distributed either volumetrically or by cost across a play, AU, or basin. Far too many unguided, non-geological, and quite arbitrary guesses have been issued by individuals or organizations that have not had the depth or sophistication, which misleads decision makers and policy makers.

How We Can Help

To make good business decisions, corporate planners, investors, economists, and upstream developers need a sophisticated and nuanced understanding of the distribution, properties, geological characteristics, recoverable volumes, and production costs of light tight oil resources in the United States. Development and delivery of such understanding is the objective of this solution.

Make no mistake; this solution is not just another “volumetric guess” at barrels of tight oil in place, akin to what we have seen in other studies (or “studies of studies”) in the past three decades. This solution is a thorough and accurate quantification of resource cost curves for unconventional oil across the various petroleum basins in the United States based on detailed probabilistic geological information and production cost and engineering fundamentals. Without such probabilistic quantification, you cannot understand the resource base, its production schedule, or costs and instead must rely on estimates with little economic or geological basis.

In this solution, using geological, production cost, and other stochastic information we are able to generate a full, complete probability density functions (pdf) over volumes to be produced in each AU coupled with the full cost to produce them (capital and operating cost). The assessment and calculation are depicted in Figure 1. Notice that we will probabilistically assess the full range of geological, well, reservoir, and production cost parameters for all light, tight oil formations and basins in the United States. The simulation is a fully probabilistic “mixing” of all the geological and cost parameters to create a joint probability distribution over producible volume in every AU and its associated production cost, as indicated on the right in Figure 1.

Figure 1: Geological Data and Cost/Volume Simulator

The output on the right, the joint pdf over producible volume and production cost, is a sophisticated joint representation of all possible cost-volume pairs for resource in each AU. It fully characterizes geological, volumetric, and cost realities and uncertainties. Figure 2 shows such a pdf (for a different basin) and evidences what the complete range of volumes and production costs within the AU weighted by their probability of occurrence looks like. (This solution generates such a pdf for every light tight oil location in the United States.) Note that the results in this case cluster the cost/volume pairs against the origin corner, i.e., the 0 volume, 0 production cost corner, but it is the specific shape of the pdf that really matters.

Figure 2: Joint Probability Density Function over Production Cost and Producible Volume

Based on the joint density in Figure 2, we use Bayesian methods to calculate the conditional probability distribution of producible volumes given the cost for each level of production. That conditional probability distribution (volume conditional on cost) appears in Figure 3.

Figure 3: Probability Distribution over Producible Volume Given Production Cost

Once we have the conditional probability distribution over volume given production cost, we can use fractile methods to calculate the probability distribution over the supply curves themselves, as shown in the Greenland example produced by Dr. Gautier and his colleagues in Figure 4. The probabilistic resource cost curve in in Figure 4, developed by Don Gautier and Red White for undiscovered oil resources in the Arctic (White and Gautier 2011), is similar to what we will develop and deliver for every light tight oil play in the United States during this project. All the probabilistic estimates and calculations will be developed as summarized here. Such a resource cost curve indicates the cumulative oil volume deliverable to the wellhead oil market for each level of production cost (Capex plus Opex) at various probabilities. Providing similar resource curves for existing and prospective light tight oil plays in the United States is the objective of this solution.

Figure 4