Prospect Analysis

Slide 11

• This is a map of how we think the HCs were distributed in the traps 10 million years ago
• The importance of the fault is clear
• If the fault can not hold (seal) the HCs, then we would have a major problem
• But if the faults do seal and form a trap, then we predict a significant amount of oil trapped at Alpha and a moderate amount of oil trapped at Beta

Slide 12

• This is a map of how we think the HCs are distributed in the traps today
• Again we are counting on the faults to act as seals to hold the HCs in the traps
• If the faults do seal and form traps, then we predict a gas cap and an oil leg at Alpha
• It looks large enough to be economic!
• We’ll have to run some numbers to be sure
• Also we predict a significant amount of oil trapped at Beta

Slide 13

• We saw this before - a simple flow chart of the work done in exploration
• We’ve gone down the workflow through Interpret Seismic Data
• The next step is to assess the prospects - to estimate its value to the company

Slide 14

• We can divide the assessment into three steps:
1. First, how much can the prospect hold – what volume of oil or gas?
2. Can we determine the fluid that the prospect holds – oil, gas or water?
3. Given our predictions, what economic value and risk is associated with the prospect?
• To convey what we do, we will work an exercise in which we do a quick assessment of Alpha and Beta

Slide 15

• I will give you some information that will help you fill in the first four lines on this table
• Then I’ll give you some more information for lines 5 and 6
• Line 6 is EUR – estimated ultimate recovery – if everything in the HC system “works”
• I’ll talk to you about how we risk a prospect – then you will fill in line 7 (blue shaded)

Slide 16

• We will make some assumptions so that we can do some simple calculations
• The sketch on the top is a cross-section through our prospect/trap
• We will use some simple trigonometry to approximate the cross-sectional area
• First we estimate the area of a large triangle formed by the top of the reservoir and the assumed fluid contact (light grey)
• Then we get the area of a smaller triangle formed by the base of the reservoir and the assumed fluid contact (dark grey)
• You know that the area of triangle = ½ base * height
• The area of the large triangle minus the area of the small triangle is an approximation of the cross-sectional area of the reservoir

Slide 17

• We have to go from an area to a volume
• Time for another simplifying assumption
• Let’s assume the trap has the basic form of one-half of a cone
• We know the volume of a cone = 1/3 (pi) r2 * h
• As you did with the area, you can estimate the conical volume from the top of the reservoir to the fluid contact and subtract the conical volume from the base of the reservoir to the fluid contact
• Use the base map to estimate the 2 radii and the 2 heights for Alpha and for Beta
• Now you can follow the instructions in the exercise and work parts 1 through 4
• Do Alpha ONLY first; if you have time and the desire, go back and do Beta

Slide 18

• In parts 1 – 4 of the exercise, we have estimated the pore space in our prospects and assumed that 80% of that space could hold HCs
• Now the question is will the HCs be oil or gas or a combination of the two
• Recall that in our data analysis unit we looked for geophysical evidence (DHI and AVO analysis)
• We have also done a lot of modeling of the HC system – timing, amount, type of HC generation, etc.

Slide 19

• We may be able to do some quantitative analysis if the rock and fluid properties are such that we expect a different seismic response for shale, water-filled sand, oil sand and gas sand
• We can also do some qualitative analyses – modeling the basin’s history and the elements of the HC system, e.g., what type of source rocks, when did they start to generate oil and gas, what volumes of oil/gas were generated within the prospect’s drainage area, do we spill oil/gas into the prospect’s drainage area, etc.
• Recall my fear of gas flushing oil out of Block 5 back in Exercise 3?

Slide 20

• We can model the seismic response we expect from sands that have different porosities and different types of fluids in their pore space
• Here we have models for sands with 10%, 20% and 30% porosity and the three types of fluids

Slide 21

• We model the seismic response as a function of offset for each model
• This allows us to determine if there are diagnostic AVO responses
• The red arrow indicates the gas-filled sand models; the green is oil sands; the blue arrow is brine sands

Slide 22

• We use the offset modeling to determine two AVO attributes that describe the variation of amplitude with offset: the “slope” and the “intercept”
• Here we have plotted these two attributes on a cross-plot
• Note the separation of the points for 10%, 20% and 30% porosity and ALSO for gas, oil and brine
• This is a “goldilocks” area – the rock and fluid properties are “just right” for AVO analysis to help us determine reservoir quality (porosity) and fluid type (gas, oil, brine)

Slide 23

• Back to Alpha and Beta…
• There are many questions that we have to answer, with lots of uncertainty
• Typically we develop our “most-likely” scenario – what seems most reasonable given the data & our experience
• We also develop a minimum and a maximum case – to indicate the range in possible results
  • e.g., the volume of the trap could be this small or that large
• For now, we will just consider the most-likely case
• Here are 5 questions that come immediately to mind
• Many times, the seismic data will give us important clues to help answer these questions

Slide 24

• Here is a seismic line across the Alpha prospect
• There is strong evidence for one fluid contact – a boundary between one type of fluid above a different type of fluid
• There is much weaker evidence for a second (shallower) fluid contact
• If there are two contacts, then the lower contact - green – is probably the boundary between oil above and water below
• The upper contact - red - is probably the boundary between gas above and oil below

Slide 25

• Now we are ready to start to determine the economic value – the heart of the assessment
• This consists of two components:
  1. How much oil or gas is there that we can get out of the reservoir, and
  2. What will its value be when we sell it
• Geoscientists and engineers work on the first part
• All oil companies have business analysts that work on the other
• It is a mystery to me how they estimate the price of a barrel of oil 8 or more years into the future
• I’m going to let this sleeping giant alone!
• For the first part – how much can we produce (get out of the ground) there are two basic approaches:
  1. a deterministic approach, and
  2. a probabilistic approach

Slide 26

• In a deterministic assessment, we assign a single number to each variable
  • e.g., the trap volume is 2750 km3, the porosity is 24%, the fluid is a medium weight oil
• The result is a single number, e.g., 200 MBO (million barrels of oil)
• In a probabilistic assessment, we assign a range of values to each variable
  • e.g., the trap volume is between 1200 and 4700 km3, the porosity is between 16% and 26%,
• The result is a range of outcomes, e.g., 200 +/- 50 MBO (million barrels of oil)

Slide 27

• For the type of fluids, we would propose different scenarios (possibilities)
• With Alpha, for example, we might propose 4 different scenarios:
1. a gas cap with an oil leg
2. a gas only reservoir
3. an oil only reservoir
4. a reservoir with mostly water but a few % gas, e.g., 95% water + 5% gas – not economic – called low gas saturation case
• Based on the data and our interpretation & analysis, we also have to assign a probability for each scenario
• In this example, our most likely is gas & oil with a 40% chance of occurrence

Slide 28

• You have been working up numbers for Alpha and Beta down through line 6
  1. First you estimated the gross rock volume in the trap (volume based on reservoir top minus volume based on reservoir base)
  2. Then you considered the fraction of that volume that would be reservoir quality (volume * net/gross)
  3. Next you used average porosity to estimate the pore volume – space for fluids
  4. Then you factored in that only 80% of the pore space would hold oil (irreducible water in the other 20%)
  5. Next was a conversion factor to go from km3 to barrels
  6. Last, we estimated how much of the total in-place oil we can hope to get to the surface (recovery efficiency) and changes in volume as the oil goes from subsurface to atmospheric pressures (fvf)
• You should have gotten about 290 MBO for Alpha and about 130 MBO for Beta
• These numbers are approximate; they depend on how well we have assigned the various numbers
• These estimates assume that all the components of the HC system has worked as we think they have
  • i.e., there is a source, it has generated large volumes of oil, there is a trap, etc.
• The next step is to discount these numbers based on risk – the chance that something did not work as we have hoped

Slide 29

• In the exercise, you worked an estimate for Alpha for the oil-only case
• We can do the same for the other 3 scenarios – scenario 4 is quite easy
• Oil and gas have different units and different values – we would like to adjust the gas to “oil-like” values
• A common conversion is that 6 GCF of gas is equivalent in value to 1 MBO
• The 4th column is labeled MOEB – million oil equivalent barrels
• For example, line 2 reports 515 GCF of gas
  • We divide 515 by 6 to get units equivalent to oil – so we get 86 MOEB
• Obviously scenario 4 (low gas saturation) is not going to make us any money
• Can we make money if one of the other scenarios is true?
• To answer this, we need to estimate the cost of producing HCs at Alpha AND the value of the oil and/or gas
• Geoscientist and engineers work up a rough estimate of the cost to produce these fields
• They team up with business analysts to decide an economic threshold.
• Let’s assume for Alpha we need a minimum of 100 MOEBs for this area to make money
• Given this economic threshold, scenarios 1 and 3 could be economic; a gas-only case would not
• Of coarse there is still the possibility that there are NO hydrocarbons at all!

Slide 30

• On the previous slide we gave each assessment parameter, like area, a single value.
• We don’t know exact values, but we can usually define a range for each parameter.
• One way to do this is to define a minimum, a maximum, and a most-likely value.
• We use statistical methods and the computer generates hundreds of possible combinations (Monte Carlo)
• We obtain a most-likely hydrocarbon volume and a range of values:
  • from the optimistic view (it could be as big as … )
  • to the pessimistic view (it could be as small as … ).

Slide 31

• From the hundreds of combinations, we can develop this plot
• It is called an excedance probability chart
• There is 100% probability of finding zero or more million barrels of oil
• This chart tells me there is a 50% chance of finding 200 MBO or more, and
• A 20% chance of finding the 275 MBO
• Given that are economic minimum is 100 MBO, there is a 75% chance of finding the economic minimum
• These are called “unrisked” results – these are OK if every component of the HC system is working, i.e., there is a source that generated HC, there is a trap, we have migration pathways, etc.

Slide 32

• This brings us to the next topic, which is risk
• Do I think everything is working at Alpha – source, reservoir, trap, seal, migration, timing, preservation?
• The pie chart indicates that my confidence level is not at 100% - more like 75%
• How do we derive this number and what do we do with it?

Slide 33

• One way to derive these numbers is to consider the 9 elements listed here: source quality, etc.
• We assemble a team composed of two types of people:
  1. People who know this area/prospect by having worked the data (e.g., from the Alpha prospect area)
  2. People who specialize in specific technical areas and have a lot of experience from many different basins (e.g., a structural geologist who has worked many fault-related traps)
• This team reviews data and interpretation, and assigns a chance of success number (COS) for all 9 on a scale from 0 to 1

Slide 34

• For Alpha, the most risky element is the trap - does the fault act as a seal.
• Another risk is that, instead of an oil or gas field, we have only low gas saturation.

The experts decide that the Alpha prospect has a 61% chance of being a success. (multiply all 9 numbers)

Slide 35

• What we would show our management is a chart like this.
• It is an excedance plot like before, with one big difference
• The maximum on the Y-axis is not 1.0; instead it is 0.61
• This is the COS that we showed on the previous slide
• That tells the boss that there is a 39% chance that the HC system is not working
• Also note the chance of having the economic minimum is a 50% - unrisked it was 75%
• The optimist would point out that there is about a 5% chance of finding 400 MOEB!

Given the quality of this prospect and its chance to make a profit compared to the other opportunities our company has, a manager will decide whether or not to add Alpha to the “To Be Drilled” list.

If Alpha is drilled and finds enough oil and gas to be economic, then we might work up the Beta prospect as a possible additional satellite development.

Slide 36

• Now we are ready to complete part 7 of Exercise 14
• We’ll use a COS of 61%
• Finish the calculations and enter a number on line 7 on the last page
• Would you propose drilling Alpha to your manager? YES - 179 MBOE is more than economic minimum
• Would you propose drilling Beta to your manager? NO - 82 MBOE is less than economic minimum