Methods and systems for quantifying an uncertainty in at least one porosity compaction model parameter are disclosed. The method includes obtaining a first sequence of depth-porosity duplets from a sedimentary layer and generating a plurality of alternate sequences of depth-porosity duplets based, at least in part, on resampling the first sequence. The method further includes estimating a plurality of values for the porosity compaction model parameter based on fitting a porosity compaction model to the first sequence and each alternate sequence. The method further includes quantifying the uncertainty in the porosity compaction model parameter based on determining the value of a parameter of probability density function fit to a histogram of the plurality of values for the porosity compaction model parameter.

The present disclosure relates to a method for determination of a real subsoil geological formation. In at least one embodiment, the method includes receiving a model representing the real subsoil, receiving a proportions cube describing geological properties of the model, determining a permeability value for a plurality of locations of the model based on the received proportions cube, determining a gradient of the flow speed based on the permeability value determined for a plurality of locations of the model, and determining a fluvial formation based on the gradient of the flow speed.

Computer-implemented stratigraphic play quality generation is disclosed. Stratigraphic data can be processed from each of a plurality of respective data sources to generate conditioned stratigraphic data. From at least some of the conditioned stratigraphic data, attributes of at least one seismic sequence can be extracted, and at least one seismic surface and at least one structural element associated with at least some of the conditioned stratigraphic data can be determined. At least some of the conditioned stratigraphic data representing sedimentary layers can be correlated with seismic reflection data to ascertain a subsurface of the geologic area at a respective depth. Reservoir properties associated with the geologic area are linked to elastic properties, and a 2D model built. Moreover, 3D map can be generated that is usable for a prospective drilling plan.

A computational stratigraphy model may be run for M mini-steps to simulate changes in a subsurface representation across M mini-steps (from 0-th subsurface representation to M-th subsurface representation), with a mini-step corresponding to a mini-time duration. The subsurface representation after individual steps may be characterized by a set of computational stratigraphy model variables. Some or all of the computational stratigraphy model variables from running of the computational stratigraphy model may be provided as input to a machine learning model. The machine learning model may predict changes to the subsurface representation over a step corresponding to a time duration longer than the mini-time duration and output a predicted subsurface representation. The subsurface representation may be updated based on the predicted subsurface representation outputted by the machine learning model. Running of the computational stratigraphy model and usage of the machine learning model may be iterated until the end of the simulation.

A water supply simulation method for interlaced system of river and canal system based on groundwater model, includes: S1. constructing simulated water conveyance channel based on first data, and performing attribute definition on water conveyance channels; S2. acquiring initial seepage, evaporation and discharge; S3. performing reverse water demand calculation; S4. performing sequential water supply simulation; S5. acquiring corresponding water head, obtaining current seepage, evaporation, discharge, head-end water demand and water consumption demand of each water conveyance channel based on water head; S6. judging whether current iteration is converged according to water head, if yes, proceeding to S7, otherwise returning to S3 after update; S7. judging whether there is next time period, if yes, returning to S3 after update, otherwise proceeding to S8; and S8. judging whether there is a next stress period, if yes, returning to S3 after update, otherwise outputting the result obtained in S5, and ending.

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.

A method for separating and quantifying gamma ray induced and neutron induced responses in a radiation detector includes detecting radiation in a radiation field comprising neutrons and gamma rays. The detected events are converted into a detector pulse amplitude spectrum. The pulse amplitude spectrum is decomposed into contributions from detected gamma rays and detected neutrons using gamma ray standard spectra and neutron standard spectra and a spectral fitting procedure which results in a best fit between a weighted sum of the contributions and the detector pulse amplitude spectrum. The fitting procedure includes determining fitting parameters for each of the standard spectra wherein at least one of the fitting parameters is different for the gamma ray standard spectra and the neutron standard spectra. In one embodiment, the fitting parameter is spectral gain.

A method may include obtaining geological data and seismic data regarding a geological region of interest, wherein the geological data includes grain size data. The method may further include determining a first set of sedimentary pathways using the grain size data. The method may further include determining a topographical surface for the geological region of interest using the seismic data or/and well data. The method may further include determining, by the computer processor, a second set of sedimentary pathways using the topographical surface. The method may further include generating various output sedimentary pathways based on a combination of the first set of sedimentary pathways and the second set of sedimentary pathways.

The present invention concerns a method for processing well data from a well. The method comprises: receiving, for each current facies, a presence probability distribution of said current facies, depending on a parameter influencing sedimentation. For each current measurement, and in a space comprising at least a first axis and a second axis, determining at least one point having, as a coordinate along the first axis, said current measurement, and as a coordinate along the second axis, a value of the parameter, determined depending on the presence probability distribution of the facies associated with the current measurement in the received well data. The method further comprises determining a curve in the space depending on at least one point for each measurement of the plurality of measurements.

A method for modelling the formation of a sedimentary area is disclosed, comprising: •—a setup step comprising defining a geological gridded model of the area comprising a plurality of cells, and setting a reference water level, •—a step of simulating the evolution of the model over a period of time, comprising: •a. assigning a water depth to each cell, •b. determining, for each cell, a direction and velocity of a water current, •c. introducing at least one particle in at least one cell of the model, •d. transporting each introduced particle in the model, based on the computed direction and velocity of the water current, comprising displacing the particle to a neighboring cell or depositing the particle in the cell, and the determination whether the particle is displaced or deposited depends on a particle granulometric class and the velocity of the water current applied to the particle, •e. updating the geological gridded model of the area according to the transport of each introduced particle.