Abstract: Exemplary implementations may: obtain, from the electronic storage, geological data corresponding to the geographic volume of interest; generate a framework for sediment deposition using a first set of multiple physical, chemical, biological, and geological processes; generate a framework for diagenesis using a second set of multiple physical, chemical, biological, and geological processes; generate a representation of sediment deposition by applying the geological data corresponding to the geographic volume of interest to the framework for sediment deposition; generate a representation of diagenesis based on the framework for diagenesis and the representation of sediment deposition; and display the representation of sediment deposition and the representation of diagenesis on a graphical user interface.

Abstract: Exemplary implementations may: obtain, from the electronic storage, geological data corresponding to the geographic volume of interest; generate a framework for sediment deposition using a first set of multiple physical, chemical, biological, and geological processes; generate a framework for diagenesis using a second set of multiple physical, chemical, biological, and geological processes; generate a representation of sediment deposition by applying the geological data corresponding to the geographic volume of interest to the framework for sediment deposition; generate a representation of diagenesis based on the framework for diagenesis and the representation of sediment deposition; and display the representation of sediment deposition and the representation of diagenesis on a graphical user interface.

Abstract: A method is described for a method for depositional modeling dependent on geological boundary conditions including receiving a process-based depositional model of a siliciclastic formation; determining a type of boundary condition at each boundary of the process-based depositional model wherein the boundary condition on at least one boundary is one of a flux-preserving boundary condition or a discrete boundary condition and wherein the boundary condition accounts for at least one of time-varying inflow of water and sediments into the process-based depositional model, time-varying outflow of water and sediments out of the process-based depositional model, and downstream controls; modeling rates of sediment and water flow over time, dependent on the boundary condition, to create a modeled depositional system; and analyzing the modeled depositional system to identify potential hydrocarbon reservoirs. The method may be executed by a computer system.

Abstract: Method for transforming a discontinuous, faulted subsurface reservoir into a continuous, fault-free space where a complete geological model based on selected geological concepts can be built and updated efficiently. Faults are removed in reverse chronological order (62) to generate a pseudo-physical continuous layered model, which is populated with information according to the selected geological concept (68). The fault removal is posed as an optimal control problem where unknown rigid body transformations and relative displacements on fault surfaces are found such that deformation of the bounding horizons and within the volume near the fault surface are minimized (63). A boundary-element-method discretization in an infinite domain is used, with boundary data imposed only on fault surfaces. The data populated model may then be mapped back to the original faulted domain such that a one-to-one mapping between continuous and faulted spaces may be found to a desired tolerance (72).

Abstract: A method is described for a method for depositional modeling dependent on geological boundary conditions including receiving a process-based depositional model of a siliciclastic formation; determining a type of boundary condition at each boundary of the process-based depositional model wherein the boundary condition on at least one boundary is one of a flux-preserving boundary condition or a discrete boundary condition and wherein the boundary condition accounts for at least one of time-varying inflow of water and sediments into the process-based depositional model, time-varying outflow of water and sediments out of the process-based depositional model, and downstream controls; modeling rates of sediment and water flow over time, dependent on the boundary condition, to create a modeled depositional system; and analyzing the modeled depositional system to identify potential hydrocarbon reservoirs. The method may be executed by a computer system.

Abstract: Method for transforming a discontinuous, faulted subsurface reservoir into a continuous, fault-free space where a complete geological model based on selected geological concepts can be built and updated efficiently. Faults are removed in reverse chronological order (62) to generate a pseudo-physical continuous layered model, which is populated with information according to the selected geological concept (68). The fault removal is posed as an optimal control problem where unknown rigid body transformations and relative displacements on fault surfaces are found such that deformation of the bounding horizons and within the volume near the fault surface are minimized (63). A boundary-element-method discretization in an infinite domain is used, with boundary data imposed only on fault surfaces. The data populated model may then be mapped back to the original faulted domain such that a one-to-one mapping between continuous and faulted spaces may be found to a desired tolerance (72).

Abstract: A method for correlating data predicted by a processor physics-based geologic model to describe a subsurface region with obtained data describing the subsurface region. Data is obtained describing an initial state of the subsurface region. Data describing a subsequent state of the subsurface region is predicted. The predicted data is compared with the obtained data taking into account whether the obtained data or the predicted data represent a discontinuous event. A sensitivity of the predicted data is determined if the predicted data is not within an acceptable range of the obtained data. The data describing the initial state of the subsurface region is adjusted based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region. A representation of the subsurface region based on the data describing the subsequent state of the subsurface region is outputted.

Abstract: A method of improving a geologic model of a subsurface region. One or more sets of parameter values are selected. Each parameter represents a geologic property. A cost and a gradient of the cost are obtained for each set. A geometric approximation of a parameter space defined by one or more formations is constructed. A response surface model is generated expressing the cost and gradient associated with each formation. When a finishing condition is not satisfied, at least one additional set is selected based at least in part on the response surface model associated with previously selected sets. Parts of the method are repeated using successively selected additional sets to update the approximation and the response surface model until the finishing condition is satisfied. Sets having a predetermined level of cost to a geologic model of the subsurface region and/or their associated predicted outcomes are outputted to update the geologic model.

Abstract: A method for correlating predicted data describing a subsurface region with obtained data describing the subsurface region is provided. Data is obtained describing an initial state of the subsurface region. Data describing a subsequent state of the subsurface region is predicted. A likelihood measure that determines whether the predicted data is within an acceptable range of the obtained data is dynamically and/or interactively updated. The predicted data is compared with the obtained data using the likelihood measure and determining a sensitivity of the predicted data if the predicted data is not within an acceptable range of the obtained data as measured by the likelihood measure. Data describing the initial state of the subsurface region is adjusted based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region. The predicted data is outputted.

Abstract: A method of improving a geologic model of a subsurface region. One or more sets of parameter values are selected. Each parameter represents a geologic property. A cost and a gradient of the cost are obtained for each set. A geometric approximation of a parameter space defined by one or more formations is constructed. A response surface model is generated expressing the cost and gradient associated with each formation. When a finishing condition is not satisfied, at least one additional set is selected based at least in part on the response surface model associated with previously selected sets. Parts of the method are repeated using successively selected additional sets to update the approximation and the response surface model until the finishing condition is satisfied. Sets having a predetermined level of cost to a geologic model of the subsurface region and/or their associated predicted outcomes are outputted to update the geologic model.

Abstract: A method for correlating predicted data describing a subsurface region with obtained data describing the subsurface region is provided. Data is obtained describing an initial state of the subsurface region. Data describing a subsequent state of the subsurface region is predicted. A likelihood measure that determines whether the predicted data is within an acceptable range of the obtained data is dynamically and/or interactively updated. The predicted data is compared with the obtained data using the likelihood measure and determining a sensitivity of the predicted data if the predicted data is not within an acceptable range of the obtained data as measured by the likelihood measure. Data describing the initial state of the subsurface region is adjusted based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region. The predicted data is outputted.

Abstract: A method for correlating data predicted by a processor physics-based geologic model to describe a subsurface region with obtained data describing the subsurface region. Data is obtained describing an initial state of the subsurface region. Data describing a subsequent state of the subsurface region is predicted. The predicted data is compared with the obtained data taking into account whether the obtained data or the predicted data represent a discontinuous event. A sensitivity of the predicted data is determined if the predicted data is not within an acceptable range of the obtained data. The data describing the initial state of the subsurface region is adjusted based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region. A representation of the subsurface region based on the data describing the subsequent state of the subsurface region is outputted.