The Source Rock Expulsion Potential Calculator:
Evaluation of a petroleum prospect requires the geologist to estimate the amount of hydrocarbons and the composition (GOR) expelled from the source rock. Current understanding stipulates that the quantity and GOR of petroleum ultimately expellable from a source rock can be determined from simple source rock parameters such as those measured in a Rock-Eval experiment.
Commonly used Rock-Eval parameters for source rock evaluation:
- TOC = organic carbon content (percent weight) of source rock.
- S1 (mg/g rock) Liquid hydrocarbon residual measured during Rock Eval (peak 1)
- S2 (mg/g rock) Liquid hydrocarbon generated by Rock Eval (peak 2)
- HI = S2/TOC (mg HC/g TOC) --- remaining organic matter/potential that can be converted to hydrocarbons.
- PI = S1/(S1+S2) a relative measure of maturity, in fraction.
- TI = S1/TOC (mg/g TOC), existing hydrocarbons (remaning in the rock). Same as BI (Bitumen Index) used in coal industry
- GOGI = Gas Prone / Oil Prone mass ratio (1.0 = 50% gas, 0.5 = 33% gas, 0.2 = 17% gas potential)
This Applet calculates the hydrocarbon expulsion potential of a source rock based on basic rock-Eval parameters. The outputs are ultimate expellable hydrocarbons from the source rock. The amount of gas versus oil expelled are based on published relationships of source data (i.e. Pepper and Corvi, 1995). The results can be used to constrain charge volumes and GOR. More sophisticated volumetric modeling can be done with KinEx to include the effects of heating rate and facies variations. Lateral geological variability and migration can be account for in Trinity . Trinity can also be used to quantify the volumes probabilistically. But, hey, this one is free (no guarantees of any kind)!
- All volumes are STP (surface) conditions. mmbls = million barrels and bcf = billion cubic feet.
- Multiply the area to the result to obtain total potential over an area.
- Divide the number by 247 to get volumes per acre (1 km2 = 247.1044 acres).
- Rock density is variable, as higher TOC rocks should have lower densities.
- This model is actually more sophisticated than just mass balance considerations. It also accounts for variability in GOR and oil API gravity, etc.
Here are some calculators for estimating original immature source rock parameters from present day mature samples. Please note that all of these methods involve assuming something that we dont know. For example, by assuming an initial hydrogen index, it will let us calculate initial TOC. The errors involved can be very large.
1) Method Based on modeled present day transformation ratio (TR)
Note: You may potentially get an original HI greater than 1150 mg/g. This may happen when TR approaches 100%. It is simply because the data and the kinetics model to calculate TR are incompatible. At 95% TR, a 5% error on TR can result in 100% error on original TOC and HI. To avoid this at high maturity, try to use averages of HI from a large number of samples.
Also watch out at high TRs, most kinetic models over estimate TR at high maturity.
2) Jarvie et al, 2007 Method
\[ TR_\text{HI} = 1 - { HI [1200-HI_o(1-PI_o)] \over
HI_o [1200-HI(1-PI)] } \]
\[ TOC_0 = { HI \left( TOC \over 1+k \right) (83.33) \over
HI_o(1-TR_\text{HI})\left[83.33-\left( TOC \over 1+k \right) \right]
- HI \left( TOC \over 1+k \right) } \]
where 83.33 is the average carbon content in hydrocarbons and k is a
correction factor based on residual organic carbon being enriched in
carbon over original values at high maturity (Burnham, 1989). For
type II kerogen, the increase in residual carbon CR at high maturity is
assigned a value of 15% (whereas for type I, it is 50%, and for type III, it
is 0%) (Burnham, 1989). The correction factor, k, is then TRHI x CR. Jarve et al, 2007, Apendix.
3) Method by Zhiyong He
\[ TOC_o = TOC { \left[ 1000-HI \cdot 0.833-TI \cdot 0.833 \over 1000-HI_o \cdot 0.833-TI_o \cdot 0.833 \right] } \]
\[ TR = 1 - { HI \cdot TOC \over HI_o \cdot TOC_o } \]
where 0.833 is the average fraction of carbon content in hydrocarbons.
Here is a quick and dirty calculator for estimating "target" oil in place (OIP) for tight reservoirs using simple Rock Eval S1 values. This is based on
Marlan Downey's 2011 AAPG presentation.
This calculator assumes 35 API oil and rock density of 2.5 g/cc. Please note that 1) S1 is part of the oil, and the heavier part of oil may not get included in S1. At high maturity, the S1 measurement may not include the lightest end of oil due to loss of volatile hydrocarbons from drilling and sampling process, in which case, an empirical correction to S1 may be needed. Using cored samples is important in this case (M. Downey et all, 2011 AAPG). Our
KinEx software provides easy and more accurate calculations, and our
Trinity software includes shale oil and gas mapping and sweet spot analysis tools.
The Tight Rock Resource Potential Calculator II:
By definition, S1 is thermally extractable part of the oil that is still in rock samples at surface, that in some cases may have bee sitting in core rooms for 30 years. Any producible petroleum has already lost while the samples travel up the bore hole to surface pressure. Below is a full calucator of resources including adsorbed petroleum and free phase. This is not subject to the above issues, but involves your assumption of in-situ HC saturation. This calculator allows you to compare the adsorbed volumes and free volumes.
References:
- Pepper, A. S., and P. J. Corvi, 1995, Simple kinetic models of petroleum formation. Part I: oil and gas generation from kerogen : Marine and Petroleum Geology, v. 12, pp.291-319.
- Pepper, A. S., and P. J. Corvi, 1995, Simple kinetic models of petroleum formation. Part III: Modeling an open system : Marine and Petroleum Geology, v. 12, n. 4 pp.417-452.
- Marlan W. Downey et al., A Quick Look Determination of Oil-in-Place in Oil Shale Resource Plays, AAPG, April 10-13, 2011, Houston
- Daniel M. Jarvie, et al., 2007, Unconventional shale-gas systems: The Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment. AAPG Bulletin, v. 91, no. 4 (April 2007), pp. 475-499
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