Total organic carbon (TOC) is the main measurement used for estimating the quality and productivity of a source rock. The source rock - usually an organic rich shale - contains various carbon compounds such as kerogen, bitumen, oil and gas. The measure of TOC in weight percent is used to quantify the potential volume of hydrocarbons in the source rock.
In a petroleum system, the source rock is the foremost element required when generating hydrocarbons. Source rock identification in seismic data is valuable to prospect assessment and risk analysis. With the introduction of unconventional resources like oil shales, source rocks have become both source and reservoir. Detecting TOC in a source rock has a great impact on source rock evaluation due to the increasing ability to estimate the TOC% in the rocks. Source rocks have a higher anisotropic signature that can be used to differentiate the organic-rich shales from the organic-poor shales. In the context of seismic data, TOC% can be detected with the relationship between organic matter, anisotropy and velocity. Figure 1 shows where TOC% has been detected using this relationship.
Lithology can be determined in the subsurface with the use of acoustic impedance (AI) – the change in density between two lithologies measured with sonic velocity. AI has a strong relationship with lithology well logs like gamma ray (GR).
Kerogen is a large insoluble molecule of organic matter deposited found in sedimentary rocks. It is the initial form of hydrocarbons, but heat and pressure cause a portion of the kerogen to be converted into a soluble form, bitumen. Bitumen is composed of oil and/or gas, as well as wax from terrestrial matter or heavy asphalt molecules.
The most well know methods to evaluate a source rock include organic geochemistry and organic petrology. Organic geochemistry involves looking at an oil that has already been produced to determine the oil’s thermal maturity, type, and generation potential using various instruments. This can be viewed as a drawback as the actual rock that has produced this oil is not looked at, unless the oil came from an unconventional well. Organic petrology uses microscopy to look at the source rock itself and the characteristics of the organic matter.
There is no perfect way to identify an organic-rich (kerogen-rich) source rock in the subsurface without core data but a few methods have been proposed. The detection and quantification of TOC% in organic-rich source rocks uses a combination of density, anisotropy, and acoustic impedance.
The elevated TOC% found in organic-rich shales tend to be highly anisotropic due to a partial alignment of already anisotropic clay minerals and bedding-parallel lamination of the organic material. The variables of seismic anisotropy occur at all scale lengths measurements are calculated for a major/minor ratio (aspect ratio). A higher aspect ratio equals a lower anisotropy while a lower aspect ratio equals a higher anisotropy. Therefore, the spherical nature of organic matter is naturally anisotropic and it is observed that this has a great effect on the source rock as is seen in the values in figure 2.
Acoustic impedance (AI) is the product of compressional p-wave velocity and density. The density of the organic-rich shale (i.e. shale with over 3% TOC) is lower than that of nonorganic-rich shales due to the fact that the density of organic matter is ~1.1-1.4 g/cm3 while the density of the average surrounding minerals is ~2.7 g/cm3. This results in a nonlinear decrease of AI with increasing TOC% as seen in figure 3. The variation of the organic matter is due to variations in the source: marine, terrestrial, etc.
The contrast between the organic and nonorganic shales remains stable down to 4500m, as seen in figure 4, where there is no longer a difference in density due to high pressures.
High anisotropy in shales leads to the presence of AVO class IV behavior – a decrease in acoustic impedance that dims with offset. There is a negative reflection coefficient at the contact between an organic-poor shale above an organic-rich source rock which dims the offset (figure 5).
Applying seismic attributes to seismic data can ease interpretations and indicate various anomalies in the data. One attribute that can identify TOC is sweetness.
S(t) = A(t) / Sqrt(fR(t))
A(t) = instantaneous amplitude
fR(t) = regularized instantaneous frequency
Conventional Vs. Unconventional Source Rocks
The use of TOC detection in source rocks is important in both conventional and unconventional reservoirs. The main difference between the two reservoirs is that a conventional reservoir holds trapped hydrocarbons that are produced from a source rock that has a high amount of TOC and has been cooked but these produced hydrocarbons must then migrate from the source rock to a trap that has both porosity and permeability while in an unconventional reservoir the source rock is the usually a trap. There are various typed of unconventional reservoirs (figure 7) and being able to identify TOC in seismic data would be helpful in all these types of reservoirs. 
TOC Detection Problems
There is not yet an effective or accurate way to measure the amount of TOC%, but the effects of anisotropy on AI, AVO, and other attributes can detect the organic matter in shales. Acoustic impedance works with extremely high TOC%’s but does not work well with lower TOC%’s. These low percentages need models to be made from one or more well logs. Also, AVO is strongly affected by changing viscoelastic effects in source rocks but viscoelastic anisotropy is difficult to accurately model.
- Steiner, S., Ahsan, S. A., Raina, I., Dasgupta, S., and Lis, G. L., (2016). Interpreting total organic carbon TOC in source rock oil plays: SPE-183050-MS, https://www.researchgate.net/publication/309758283_Interpreting_Total_Organic_Carbon_TOC_in_Source_Rock_Oil_Plays
- Amato del Monte, A., Antonielli, E., De Thomas, V., Luechetti, G., and Gambacorta, G., 2018, Methods for source rock identification on seismic data: An example from the Tanezrouft Formation (Tunisia): Marine and Petroleum Geology, 91, 108-124, https://www.sciencedirect.com/science/article/pii/S0264817217304968
- Loseth, H., Wensaas, L., Gading, M., Duffaut, K., and Springer, M., 2011, Can hydrocarbon source rocks be identified on seismic data? Geology, 39, no 12, 1167-1170, https://pubs.geoscienceworld.org/gsa/geology/article/39/12/1167/130467/can-hydrocarbon-source-rocks-be-identified-on
- Sayers, C. M., Gou, S., and Silva, J., 2013, Sensitivity of the elastic anisotropy and seismic reflection amplitude of the Eagle Ford Shale to the presence of kerogen: Geophysical Prospecting, 63, 151-165, https://onlinelibrary.wiley.com/doi/full/10.1111/1365-2478.12153
- Sayers, C. M., 2013, The effect of kerogen on the AVO response of organic-rich shales: The Leading Edge, 32, no 12, 1514-1519, https://library.seg.org/doi/abs/10.1190/tle32121514.1
- Ogiesoba, O. and Hammes, U., (2010). Understanding lithologic signiface of amplitude envelope and acoustic impedance within Oligocene and Miocene strata, South Texas Gulf Coast. Search and Discovery, 40577 http://www.searchanddiscovery.com/documents/2010/40577ogiesoba/ndx_ogiesoba.pdf
- Vandenbroucke, M. and Largeau, C. (2007). Kerogen origin, evolution and structure. Organic Geochemistry. 38(5), 719-833. https://www.sciencedirect.com/science/article/pii/S014663800700006X
- (2016). Unconventional resources [PPT]. http://pages.geo.wvu.edu/~jtoro/Petroleum/24_Unconventional-1.pdf