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  5. Size of the Prize

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- Today, in this presentation series, we discuss the various geologic elements and their risks associated with the hydrocarbon trap. In this presentation, we'll discuss the size of the prize. Assuming all of the geologic elements are in place for our prospect, how much oil and/or gas is in place, and how much of that hydrocarbon can be produced? As with previous presentations, finding the quantity of hydrocarbons that are in place and that can then be produced is a critical topic with a great deal of in depth knowledge required. Today's presentation will be an introduction into another critical element required for successful oil and gas exploration, that again, requires in depth knowledge. There is seven individual factors that go into defining the final answer. That answer being how much oil or gas can I expect to produce from this prospect? First, we have gross rock volume, or GRV, how large is the greater trap? This volume, which is measured in units such as acre-feet or cubic meters, is defined via subsurface mapping of the greater area and then defining what area is deemed a trap. This volume can be measured using various methods from hand planimetry and volumes and then semi-nodes, to digital volumetrics based on digital maps. Next, we define net rock volume. Just because volume of rock is within a closure or a trap does not mean it's a reservoir. A geologic model is developed based on local information in the form of subsurface wells or core data to justify the amount of reservoir to be expected in a particular prospect. The definition of this value can vary from being very speculative in areas where we have small amounts of information to relatively precise estimations in areas with more robust databases. As with gross rock voulme, net rock volume is measured in acre-feet or cubic meters, and many times is defined as a percentage of the gross rock volume value. Next, we have pore volume. Pore volume is known as porosity and it's that portion of the reservoir that is void of rock and thus capable of containing either fluids or gas. As with all these values, porosity can be defined in a number of different ways depending on amount of associated data that we have to define it. In immature areas, with limited data, it's possible to have a single value for porosity for a prospect. In more mature areas with larger data sets and more sophisticated subsurface models, porosity can vary both vertically and laterally and be defined as part of a three-dimensional model. Now, the pore volume is measured as a percentage of the net rock volume available, and can vary in values as low as 5% in tight reservoirs to greater than 30% in clean and consolidated reservoirs. Saturation. As previously mentioned, pore space, or porosity, must be filled with some fluid or gas, but that does not have to be hydrocarbons. There is always a certain percentage of the pore space that will be filled with water, and there is always an opportunity to have gases other than hydrocarbons in that pore volume. That's our objective, is to produce hydrocarbons. It's important to estimate the amount of saturation of hydrocarbons in the available pore space. Saturation, then, is a measure of the available pore space that is filled with hydrocarbons. In-place volumes. With the four mentioned factors defined, the volume of oil in place can be calculated. It's very important, when making this calculation, that units are properly addressed. Conversion factors need to be properly introduced such that volumes that were previously in acre-feet or cubic meters can be converted into, say, barrels, in an oil case. An example of an in-place equation that converts acre-feet into barrels is shown below. In this equation, we have OOIP, or original oil in-place and those units are going to be barrels. Then we have 7758, which is a conversion factor that takes acre-feet and converts it into barrels. Then we have gross rock volume, GRV, which is the gross volume of our prospect and it's measured in acre feet. Net to gross, NG, this is the portion of the gross rock volume that is actually reservoir. Then we have porosity symbol. This is a measure of the percentage of the reservoir that's actually void space. 1 minus Sw gives us the saturation of hydrocarbons, that's 1 minus the saturation of water, and finally, we have B-sub-o, which is the formation volume factor. This is associated with the actual properties of the oil in the reservoir, and is defined in the laboratory. EUR, or expected ultimate recovery, unrisked, is our next topic. We've calculated what the hydrocarbon in-place volume is but that's not really what we want to know. Our major concern is not how much is in place but how much of the in-place hydrocarbon can actually be produced. We determine this by defining a recovery factor. Now, like most of the values in these estimations, recovery factor can vary wildly. In tight reservoirs with no stimulation, recovery factor can be less than 10%. In good reservoirs with light hydrocarbons or gas, recovery factor can be as high as 85%, so you see this factor is wildly variable and needs to be determined to determine the viability of our prospect. Our final calculation is defining the risked EUR, or expected ultimate recovery risked. Risked EUR is simply the EUR that was previously defined multiplied by the GCOS, or geologic chance of success that we previously defined. Risked EUR is a very valuable value in the fact that it allows for management to compare prospects of different sizes on a more even playing field. As an imaginary example, let's take company Oil who has two prospects that it can drill but can only budget to drill one of them. The first prospect, prospect A, is large, with 100 million barrels of EUR, but it's also in an area that's much less well explored, much less well understood, so its GCOS or geologic chance of success is only 20%, making its EUR risk 20 million barrels. In comparison, we have prospect B that's much more mature area. As such, its GCOS is much lower, only 80%. The size of the prospect is 50 million barrels but when we multiply 80% chance of success by 50 million barrels, you see we come up with 40 million barrels, so, this allows management to compare a high risk, high reward prospect with a lower risk, smaller prospect. The equation for defining, or estimating the original oil in place was presented in the last slide. Now, there are two general methods for using this equation to go about making our OOIP assessment. The first of these is known as deterministic assessment. When using the deterministic approach, one single value is assigned for each one of the variables in the equation, thus resulting in a single value or our OOIP. This result is fairly easy to define and gives a specific value for a final answer that is most probably wrong. Geology of any area is variable and we always have an incomplete knowledge of those variations. As such, by assigning a single value for each one of these variables, we're going to end up with an assessment that is most probably incorrect. The second method for defining the OOIP volumes is known as a probabilistic assessment. When using a probabilistic method, a range of values, rather than a single value, is used for each one of the variables, and then statistical method is used to run hundreds of possibilities, maybe even thousands, in what is known as Monte Carlo's simulation. Based on the initial endpoints, or midpoint values that have been defined for each of the variables, a range of possible final volumes is determined along with the probability of each of those volumes being realized. By analyzing this final OOIP volume range, one can determine if it satisfies the economics for your project. The downside of using a probabilistic assessment is that it requires computer software to run the Monte Carlo simulation, and it's far more complicated, with many more variables, than a simple deterministic method. There's also the fact that just because you run a Monte Carlo simulation and end up with a set of statistics, that that set of statistics is reasonable. Remember, junk in equals junk out. This graph portrays the results of a hypothetical probabilistic assessment for prospect alpha. Hundreds of combinations were run, using a Monte Carlo simulation software to create this probabilistic chart. Note that on the vertical axis, we're representing the probability of each of the particular situations taking place. On the horizontal axis, we see the volumes of hydrocarbons associated with each of those probabilities. Starting on the far left side of the chart, you'll see there's a 100% probability of finding at least no oil. As we progress to the right, the amount of in-place oil increases and the chance of finding that oil decreases until we reach the far right side of the chart at which point we find there's zero chance of finding greater than 350 million barrels in place. Other key points on this chart that need to be highlighted are the fact that there's a 75% chance of finding at least 100 million barrels which is what we've defined as our economic limit. There's also a 50% chance of finding 200 million barrels or greater which would make this a very attractive project. As previously mentioned, but what needs to be emphasized is the fact that these results are based on values that were used as input assumptions. If those input assumptions are invalid, this result is as well. Again, garbage in equals garbage out. It should further be mentioned that these values are unrisked. GCOS, or geologic chance of success, needs to be applied before a final decision is made.