The Silurian Qusaiba Hot Shales of Saudi Arabia: An integrated assessment of thermal maturity

The Lower Silurian Qusaiba Hot Shales (QHS) are proven source rocks for oil within the Paleozoic, and possibly some of the Mesozoic, reservoirs in Saudi Arabia. Moreover, these shales have oil shale potential where they are immature and shallow enough for mining, as well as unconventional shale oil and shale gas potential, in areas where they are within oil-maturity and gas-maturity levels, respectively. The QHS were deposited in relatively shallow marine environments under anoxic water conditions, resulting in accumulation of amorphous kerogen, organic-walled graptolites and acritarchs. Across the Arabian Basin, organic matter quality does not show much variation for the QHS, but the maturity varies greatly as a result of varying burial history.Thermal maturity assessment of shale source rocks that lack vitrinite, such as the Qusaiba Hot shales, continues to be challenging, especially where conflicting measurements are obtained from different sources.This paper presents an integrated assessment of QHS thermal maturity parameters, based on cores from 13 carefully selected boreholes that - based on regional basin models - are believed to cover a wide maturity range (ca. 0.5 to 2.0% Ro). We conducted some analyses on kerogen (maceral petrography, graptolite reflectance, UV-fluorescence, whole rock pyrolysis, Raman spectroscopy of graptolite) and other analyses on bitumen extracts (GC and GC-MS of saturate and aromatic fractions, and FTIR spectroscopy of the asphaltene fraction). We show that using many thermal maturity parameters reduces uncertainty significantly, and we therefore recommend that graptolite reflectance analyses should be conducted in support of other maturity indicators. Proper reflectivity measurements of the graptolites set the reference for comparison of other maturity parameters obtained from petrographic, geochemical, and spectroscopic techniques. Our work provides a template by which Qusaiba thermal maturity can be more accurately estimated when only a limited set of maturity parameters is available.