Deciphering the diagenetic history of the El Abra Formation of eastern Mexico using reordered clumped isotope temperatures and U-Pb dating

Carbonates form ubiquitously throughout the history of deposition, burial, and uplift of basins. As such, they potentially record the environmental conditions at the time of formation. Carbonate clumped isotopes provide the temperature of precipitation but can be internally reordered if the host rock is exposed to elevated temperatures over geologic time scales. Here, we exploited this kinetic behavior by analyzing multiple generations of cements that capture the range of environments experienced by the El Abra Formation from eastern Mexico. From this, we developed a quantitative diagenetic history for these different phases of cementation. We observed a 70 °C range in clumped isotope temperatures from 64 °C to 134 °C for these cements, which is not compatible with their inferred precipitation environments. This suggests that bond reordering occurred during burial but did not fully reorder all cements to a common apparent temperature. We reconstructed original cement growth temperatures and the isotopic signature of the parent fluids to show that precipitation from a marine pore fluid began at 125 Ma, contemporaneous with deposition, and continued throughout burial to temperatures of at least 138 °C at 42 Ma. We show that precipitation of equant cements, which occluded 90% of the pore space, was coincident with Laramide-related burial to depths greater than 3800 m. A U-Pb age of diagenetic calcite of 77.1 ± 3.6 Ma provides independent support for our estimates of the absolute timing of precipitation of two distinct phases of the paragenesis. This is the first demonstration of the utility of integrating U-Pb age dating with reordered clumped isotope temperatures to provide quantitative constraints on the time-temperature history of cementation. Such information may ultimately lead to advances in our understanding of the formational environments and geological processes that drive diagenesis in carbonates for temperatures below the clumped isotope “blocking temperature.

Gas geochemistry of the Mobile Bay Jurassic Norphlet Formation: Thermal controls and implications for reservoir connectivity

The Mobile Bay gas field is located offshore Alabama in the northern Gulf of Mexico. Production is from eolian dunes of the Jurassic Norphlet sandstone at depths exceeding 6100 m (gt20,000 ft) and temperatures greater than 200degC. Reservoir connectivity and compositional variation, including the distribution of nonhydrocarbon gases (H2S and CO2), are critical factors in production strategy. To evaluate the controls on compositional variation and connectivity, detailed molecular and isotopic analyses were conducted for 29 wells. Analysis of volatiles in fluid inclusions suggests that the field was originally filled with oil that subsequently cracked to gas. In addition to the thermal destruction (cracking) of oil, the process of thermochemical sulfate reduction (TSR) continues to destroy the remaining hydrocarbons through oxidation of gas and reduction of sulfate to form H2S and CO2. The variable extent of the TSR process at Mobile Bay results in a wide range of hydrocarbon and H2S compositions. Condensates are almost exclusively composed of diamondoids whose composition appears controlled by H2S concentrations. In contrast to hydrocarbon and H2S contents, CO2 concentrations are relatively constant throughout the field. Carbon isotopic ratios for CO2 correlate positively with those for wet-gas hydrocarbons but are heavier than expected for CO2 originating from hydrocarbon oxidation via TSR. The narrow range of CO2 contents and heavy isotope ratios suggests that CO2 is regulated by water-rock equilibration and carbonate precipitation. The destruction of the hydrocarbon gas and mineralization of the carbon dioxide product create a volume reduction and an associated drop in reservoir pressure. This process creates several internal sinks (or exits) that may control the spill direction for gas in the field

Looking Back to the Future: Predicting <i>in Vivo</i> Efficacy of Small Molecules versus <i>Mycobacterium tuberculosis</i>

Selecting and translating <i>in vitro</i> leads for a disease into molecules with <i>in vivo</i> activity in an animal model of the disease is a challenge that takes considerable time and money. As an example, recent years have seen whole-cell phenotypic screens of millions of compounds yielding over 1500 inhibitors of Mycobacterium tuberculosis (<i>Mtb</i>). These must be prioritized for testing in the mouse <i>in vivo</i> assay for <i>Mtb</i> infection, a validated model utilized to select compounds for further testing. We demonstrate learning from <i>in vivo</i> active and inactive compounds using machine learning classification models (Bayesian, support vector machines, and recursive partitioning) consisting of 773 compounds. The Bayesian model predicted 8 out of 11 additional <i>in vivo</i> actives not included in the model as an external test set. Curation of 70 years of <i>Mtb</i> data can therefore provide statistically robust computational models to focus resources on <i>in vivo</i> active small molecule antituberculars. This highlights a cost-effective predictor for <i>in vivo</i> testing elsewhere in other diseases