20 Feb Create a Gas In Place (OGIP) distribution, determining the P10, P50 & P90 values using the following hints. Document your results
Create a Gas In Place (OGIP) distribution, determining the P10, P50 & P90 values using the following hints. Document your results in a 2 page report with key screen shots. Also upload your @Risk excel sheet.
a. Use the HW3_OGIP.XLS spreadsheet which has two tabs:
i. Welldata – this is the raw data from 25 wells in the same field.
ii. VolumetricModel – this is where the calculations reside for that field.
b. In the VolumetricModel tab, replace the Input Values for Depth, Thickness, GC, Density, PhiM, and Sw with distribution functions from @Risk. To obtain the distributions functions, go first to the WellData TAB.
c. In the WellData tab, choose a distribution function — for each of these inputs — that you think adequately matches the data. Be careful of using functions that result in nonsensical values (i.e. negative thickness; use RiskTruncate).
d. In the VolumetricModel tab, replace the OutputValue for GIPTotal with a RiskOutput function.
e. Run the Monte Carlo simulation utilizing the distributions of input variables and the single output variable GIPTotal to generate the distribution for GIPTotal and the P10, P50 and P90 estimates. Use at least 1000 iterations.
PalisadeFitLinks
| Num Links | 4 |
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WellData
| Pore pressure | Normal hydrostatic | |||||
| Reservoir temperature | 100 | deg f | ||||
| Gas gravity | 0.62 | |||||
| CO2, mole fraction | 2.1% | |||||
| N2, mole fraction | 1.1% | |||||
| Well | Depth, ft | Shale thickness, ft | Gas content, scf/ton | Rock density, gm/cc | Matrix porosity, % | Matrix Sw, % |
| Well001 | 2,592 | 107.7 | 47.2 | 2.466 | 2.20% | 48.1% |
| Well002 | 2,428 | 107.7 | 2.416 | |||
| Well003 | 2,076 | 198.3 | 57.0 | 2.488 | 1.40% | 49.7% |
| Well004 | 2,284 | 130.8 | 50.1 | 2.511 | 1.70% | 49.9% |
| Well005 | 2,280 | 177.3 | 2.471 | |||
| Well006 | 2,106 | 90.0 | 69.8 | 2.465 | 4.30% | 50.4% |
| Well007 | 2,184 | 160.5 | 50.0 | 2.447 | 2.10% | 50.0% |
| Well008 | 2,365 | 90.0 | 80.6 | 2.462 | 2.10% | 42.4% |
| Well009 | 2,124 | 108.6 | 2.413 | |||
| Well010 | 2,301 | 93.6 | 2.445 | |||
| Well011 | 2,044 | 163.5 | 52.6 | 2.439 | 2.00% | 44.5% |
| Well012 | 2,417 | 148.8 | 63.6 | 2.428 | 2.80% | 48.1% |
| Well013 | 2,150 | 178.8 | 2.508 | |||
| Well014 | 2,305 | 132.3 | 71.6 | 2.410 | 2.30% | 49.7% |
| Well015 | 2,494 | 89.4 | 46.7 | 2.489 | 2.80% | 45.0% |
| Well016 | 2,277 | 121.8 | 2.440 | |||
| Well017 | 2,447 | 120.6 | 2.365 | |||
| Well018 | 2,078 | 108.0 | 62.7 | 2.467 | 2.10% | 45.2% |
| Well019 | 2,295 | 132.6 | 2.386 | |||
| Well020 | 2,216 | 135.0 | 2.427 | |||
| Well021 | 2,104 | 138.0 | 78.3 | 2.408 | 1.80% | 45.0% |
| Well022 | 2,195 | 111.9 | 63.8 | 2.520 | 2.10% | 44.0% |
| Well023 | 1,998 | 79.5 | 2.510 | |||
| Well024 | 2,086 | 175.5 | 94.4 | 2.388 | 1.60% | 46.2% |
| Well025 | 2,060 | 88.8 | 52.1 | 2.444 | 2.40% | 49.4% |
VolumetricModel
| Inputs | |||||
| Depth | 2,274 | ft | |||
| Pressure | 985 | psia | |||
| Thickness | 89.0 | ft | |||
| GC | 58.0 | scf/ton | |||
| Density | 2.488 | gm/cc | |||
| Phim | 2.12% | ||||
| Sw | 43.5% | ||||
| Bg | 0.00293 | RB/Mscf | |||
| Outputs | |||||
| GIPsorbed | 10.37 | Bscf/sec | Factor 62.4 from density gm/cc to lbm per cubic ft; 1 US ton is 2000 lbm (US pound mass) | ||
| GIPfree | 1.75 | Bscf/sec | Factor 5.615 from barrels to cubic ft (converting RB to cubic ft, as in Bg) | ||
| GIPtotal | 12.12 | Bscf/sec |
,
PETE 555
HW 3
a. Use the HW3_OGIP.XLS spreadsheet which has two tabs:
i. Welldata – this is the raw data from 25 wells in the same field.
ii. VolumetricModel – this is where the calculations reside for that field.
b. In the VolumetricModel tab, replace the Input Values for Depth, Thickness, GC, Density, PhiM, and Sw with distribution functions from @Risk. To obtain the distributions functions, go first to the WellData TAB.
c. In the WellData tab, choose a distribution function — for each of these inputs — that you think adequately matches the data. Be careful of using functions that result in nonsensical values (i.e. negative thickness; use RiskTruncate).
d. In the VolumetricModel tab, replace the OutputValue for GIPTotal with a RiskOutput function.
e. Run the Monte Carlo simulation utilizing the distributions of input variables and the single output variable GIPTotal to generate the distribution for GIPTotal and the P10, P50 and P90 estimates. Use at least 1000 iterations.
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