Abstract: A geological projection system may receive seismic survey data, the seismic survey data including a seismic surface of a geological feature. A geological projection system may receive resistivity sensor data from a downhole resistivity sensor, the resistivity sensor data being for a reference length uphole of a reference depth. A geological projection system may generate a sensed surface over the reference length using the resistivity sensor data. A geological projection system may generate a displacement field of a difference between the sensed surface and the seismic surface for the reference length. A geological projection system may apply an uncertainty model to at least one of the resistivity sensor data, the seismic survey data, or the displacement field, the uncertainty model generating an output including an uncertainty distribution of a projected surface of the geological feature downhole of the reference depth.

Abstract: A method can include selecting a type of geophysical data; selecting a type of algorithm; generating synthetic geophysical data based at least in part on the algorithm; training a deep learning framework based at least in part on the synthetic geophysical data to generate a trained deep learning framework; receiving acquired geophysical data for a geologic environment; implementing the trained deep learning framework to generate interpretation results for the acquired geophysical data; and outputting the interpretation results.

Abstract: A method can include selecting a type of geophysical data; selecting a type of algorithm; generating synthetic geophysical data based at least in part on the algorithm; training a deep learning framework based at least in part on the synthetic geophysical data to generate a trained deep learning framework; receiving acquired geophysical data for a geologic environment; implementing the trained deep learning framework to generate interpretation results for the acquired geophysical data; and outputting the interpretation results.

Abstract: A method is provided for constraining a seismic inversion using real-time measurements. The method comprises: receiving a seismic signal/seismic data; obtaining logging-while-drilling (LWD) measurements made during a drilling procedure; using the LWD measurements to constrain an inversion of the seismic signal/data; and using the inverted seismic signal/data to: obtain an image of a subterranean section of the Earth, determine properties of the subterranean section of the Earth and/or update a model of the subterranean section of the Earth.

Abstract: A method of analysing the dynamic behavior of fracture networks in a seismic volume is provided. The method includes providing a plurality of seismic time lapse vintages of the same geological volume; identifying and parameterising fractures within fracture networks of each vintage; determining one or more distributions of fracture parameters for the fracture networks of each vintage; and identifying changes to the fracture networks by comparing corresponding distributions across the vintages.

Abstract: A method of processing stratigraphic data comprising a plurality of stratigraphic features, such as horizon surfaces, within a geological volume is provided. The method includes the steps of: extending a plurality of spaced sampling traces through the volume to traverse the stratigraphic features; and assigning the stratigraphic features respective relative geological ages. On each sampling trace, the relative geological age of each stratigraphic feature traversed by the sampling trace in the direction from geologically younger to geologically older stratigraphic features is increased in relation to the relative geological age of its preceding stratigraphic feature, under the condition that each stratigraphic feature takes the same relative geological age across all the sampling traces by which it is traversed.

Abstract: A method of analysing the dynamic behaviour of fracture networks in a seismic volume is provided. The method includes providing a plurality of seismic time lapse vintages of the same geological volume; identifying and parameterising fractures within fracture networks of each vintage; determining one or more distributions of fracture parameters for the fracture networks of each vintage; and identifying changes to the fracture networks by comparing corresponding distributions across the vintages.

Abstract: A method of processing stratigraphic data comprising a plurality of stratigraphic features, such as horizon surfaces, within a geological volume is provided. The method includes the steps of: extending a plurality of spaced sampling traces through the volume to traverse the stratigraphic features; and assigning the stratigraphic features respective relative geological ages. On each sampling trace, the relative geological age of each stratigraphic feature traversed by the sampling trace in the direction from geologically younger to geologically older stratigraphic features is increased in relation to the relative geological age of its preceding stratigraphic feature, under the condition that each stratigraphic feature takes the same relative geological age across all the sampling traces by which it is traversed.

Abstract: A method for automated extraction of surface primitives from seismic data is presented. A preferred embodiment of the method includes defining, typically with sub-sample precision, positions of seismic horizons through an extrema representation of a 3D seismic input volume; deriving coefficients that represent the shape of the seismic waveform in the vicinity of the extrema positions; sorting the extrema positions into groups that have similar waveform shapes by applying classification techniques with the coefficients as input attributes using unsupervised or supervised classification based on an underlying statistical class model; and extracting surface primitives as surface segments that are both spatially continuous along the extrema of the seismic volume and continuous in class index in the classification volume.

Abstract: A method for automated extraction of surface primitives from seismic data is presented. A preferred embodiment of the method includes defining, typically with sub-sample precision, positions of seismic horizons through an extrema representation of a 3D seismic input volume; deriving coefficients that represent the shape of the seismic waveform in the vicinity of the extrema positions; sorting the extrema positions into groups that have similar waveform shapes by applying classification techniques with the coefficients as input attributes using unsupervised or supervised classification based on an underlying statistical class model; and extracting surface primitives as surface segments that are both spatially continuous along the extrema of the seismic volume and continuous in class index in the classification volume.