Abstract: A method for retrodicting source-rock quality and/or paleoenvironmental conditions are disclosed. A first set of system variables associated with source-rock quality is selected (705). A second set of system variables directly or indirectly causally related to the first set of variables is also selected (710). Data for variables selected to be known quantities are estimated or obtained (720). A network with nodes including both sets of variables is formed (715). The network has directional links connecting interdependent nodes (715). The directional links preferably honor known causality relations. A Bayesian network algorithm is used with the data to solve the network for the unknown variables and their associated uncertainties (725). The variables selected to be unknowns can be input nodes (paleoenvironmental conditions), intermediate nodes, output nodes (source rock quality), or any combination thereof.

Abstract: Method for assessing hydrocarbon source rock potential of a subsurface region without well log information. The method uses surface electromagnetic (121) and seismic (122) survey data to obtain vertical profiles of resistivity and velocity (123), which are then analyzed in the same way as well log data are analyzed by the well known Delta Log R method (124).

Abstract: Method for assessing hydrocarbon source rock potential of a subsurface region without well log information. The method uses surface electromagnetic (121) and seismic (122) survey data to obtain vertical profiles of resistivity and velocity (123), which are then analyzed in the same way as well log data are analyzed by the well known DeltaLogR method (124).

Abstract: A method for retrodicting source-rock quality and/or paleoenvironmental conditions are disclosed. A first set of system variables associated with source-rock quality is selected (705). A second set of system variables directly or indirectly causally related to the first set of variables is also selected (710). Data for variables selected to be known quantities are estimated or obtained (720). A network with nodes including both sets of variables is formed (715). The network has directional links connecting interdependent nodes (715). The directional links preferably honor known causality relations. A Bayesian network algorithm is used with the data to solve the network for the unknown variables and their associated uncertainties (725). The variables selected to be unknowns can be input nodes (paleoenvironmental conditions), intermediate nodes, output nodes (source rock quality), or any combination thereof.

Abstract: A method for accelerating the conversion of kerogen to hydrocarbons in a subterranean formation containing organic-rich rock that is located in the vicinity of reservoir-quality strata. Sufficient heat is generated in the reservoir-quality strata such that it heats the organic-rich rock in the subterranean formation and accelerates the conversion of kerogen to hydrocarbons in the formation.

Abstract: A method for accelerating the conversion of kerogen to hydrocarbons in a subterranean formation containing organic-rich rock that is located in the vicinity of reservoir-quality strata. Sufficient heat is generated in the reservoir-quality strata such that it heats the organic-rich rock in the subterranean formation and accelerates the conversion of kerogen to hydrocarbons in the formation.