An x-ray based litho-density tool for measurement of formation surrounding a borehole is provided, the tool including at least an internal length comprising a sonde section, wherein said sonde section further comprises an x-ray source; at least one radiation measuring detector; at least one source monitoring detector; a plurality of sonde-dependent electronics; and a reference detector, wherein the reference detector is used to monitor the output of the x-ray source such that the reference detector's output effects corrections to the outputs of the detectors used to measure the density of the materials surrounding the borehole in order to correct for variations in the x-ray source output. Tool logic electronics, PSUs, and one or more detectors used to measure borehole standoff such that other detector responses maybe compensated for tool standoff are also provided. Shielding, through-wiring; wear-pads that improve the efficacy and tool functionality are also described and claimed.

An x-ray based litho-density tool for measurement of formation surrounding a borehole is provided, the tool including at least an internal length comprising a sonde section, wherein said sonde section further comprises an x-ray source; at least one radiation measuring detector; at least one source monitoring detector; a plurality of sonde-dependent electronics; and a reference detector, wherein the reference detector is used to monitor the output of the x-ray source such that the reference detector's output effects corrections to the outputs of the detectors used to measure the density of the materials surrounding the borehole in order to correct for variations in the x-ray source output. Tool logic electronics, PSUs, and one or more detectors used to measure borehole standoff such that other detector responses may be compensated for tool standoff are also provided.

Shielding, through-wiring, wear-pads that improve the efficacy and tool functionality are also described and claimed.

A method for determining a thermal maturity image of a subterranean region and a non-transitory computer readable medium, storing instructions for executing the method, are disclosed. The method includes, obtaining a seismic dataset for the subterranean region of interest, obtaining a thermal maturity value for a plurality of core samples taken from different positions within the subterranean region, and obtaining a plurality of well log types from the core sampling location. The method further includes determining a calibrated rock physics model based on the plurality of well log types, determining a pore fluid type based on the calibrated rock physics model, and determining a thermal maturity model based on the plurality of core samples, on the pore fluid type, and on the plurality of well logs. The method still further includes determining the thermal maturity image of the subterranean region based on the seismic dataset and thermal maturity model.

A long-term in-situ observation device for the deep sea bottom supported engineering geological environment is provided, including: a sediment acoustic probe, a sediment pore water pressure probe, a three-dimensional resistivity probe, a water observation instrument, a long-term observation power supply system, a probe hydraulic penetration system, a general control and data storage transmission system, an acoustic releaser, an underwater acoustic communication apparatus, and an instrument platform. The observations include the engineering properties, physical properties, mechanical properties, and biochemical properties of a seawater-seabed interface-sediment. The engineering properties and the physical and mechanical indexes of seafloor sediments are comprehensively determined by three-dimensional measurement of seafloor resistivity and acoustic wave measurements. The physical and biochemical properties of seawater are expected to be acquired by sensors. The observation probe penetrates into the sediments following the hydraulic method.

A computer-implemented method, and system implementing the method, are disclosed for computing a final model of elastic properties, using nonlinear direct prestack seismic inversion for Poisson impedance. User inputs and earth-model data is obtained over points of incidence of a survey region, at various angles of incidence. Various models are then computed that serve for lithology identification and fluid discrimination and take part in preliminary seismic exploration and reservoir characterization. Therefore, further refinement of these models is required due to changes in burial depths, compaction and overburden pressure, as they provide limitations for reservoirs on porous media. The further refinement using nonlinear direct prestack seismic model is performed on a system computer, which produces a final model of elastic properties. This model can then be applied for lithology prediction and fluid detection to identify potential targets of oil and gas exploration and estimating spots in unconventional shale gas applications.

A reflection full waveform inversion method updates separately a density model and a velocity model of a surveyed subsurface formation. The method includes generating a model-based dataset corresponding to the seismic dataset using a velocity model and a density model to calculate an objective function measuring the difference between the seismic dataset and the model-based dataset. A high-wavenumber component of the objective function's gradient is used to update the density model of the surveyed subsurface formation. The model-based dataset is then regenerated using the velocity model and the updated density model, to calculate an updated objective function. The velocity model of the surveyed subsurface formation is then updated using a low-wavenumber component of the updated objective function's gradient. A structural image of the subsurface formation is generated using the updated velocity model.

A method for modelling and migrating seismic data, that includes using an acoustic wave equation and a spatial distribution of one or more earth-model parameters. The acoustic wave equation is modified by including at least one secondary source term, and based on a seismic acquisition configuration, either calculating the seismic signals that would be detected from the modelled wavefield or migrating observed seismic signals or migrating residual signals as part of an inversion.

A method is disclosed that includes obtaining a seismic data set and a seismic wave propagation velocity model and approximating the seismic wave propagation velocity model as a plurality of layers each bounded by a first and second bounding depth. For each of the plurality of layers, the method includes: simulation of the propagation of a seismic wave through the layer using a two-way seismic wave propagation simulator; forming an over-determined system of linear equations relating at least one mono-frequency component of the seismic wave at the first depth to one mono-frequency component at the second depth; and determining a plurality of one-way seismic wave propagation operators by inverting the over-determined system of linear equations. The method further includes processing the seismic data set using the one-way seismic wave propagation. A system and a non-transitory computer readable medium for implementing the method are also disclosed.

A method, a system, and a non-transitory computer readable medium to calibrate a lithostatic stress map of a particular geological layer in a basin model are described. The lithostatic stress map is generated by simulating the basin model and calibrated based on available well data without re-simulating the basin model. In particular, the calibration is based on the mean lithostatic density, which is a constant value of density that yields a value of lithostatic stress equivalent to the lithostatic stress at the same depth produced by the existing column of rocks in the basin.

Systems and methods are disclosed that include generating reservoir property profiles corresponding to reservoir properties for pseudo wells based on reservoir data, generating seismic attributes for the pseudo wells, and training a machine learning model by comparing the reservoir property profiles against the seismic attributes. In this manner, the machine learning model may be used to predict reservoir properties for use with seismic exploration above a region of a subsurface that contains structural or stratigraphic features conducive to a presence, migration, or accumulation of hydrocarbons.