It discloses an experimental apparatus and experimental method for physical modeling of a fluid migration and accumulation process with contemporaneous structural deformation. The experimental apparatus comprises a structural deformation experiment box, a structural deformation control device, a fluid control device and an experimental control device; the structural deformation experiment box is installed in a basket experiment module on a cantilever of a drum centrifuge, the structural deformation control device can extend and compress an experimental model in horizontal and vertical directions; and fluid cylinders of the fluid control device can be filled with fluids or plastic materials.

A method and apparatus for generating a fluid saturation model for a subsurface region. One example method generally includes obtaining a model of the subsurface region; for each of a plurality of fluid types: flooding the subsurface region model with the fluid type to generate a flood model; and running a trial petrophysical inversion with the flood model to generate a trial petrophysical model; identifying potential fluid contact regions in the trial petrophysical models; partitioning the subsurface region model at the identified potential fluid contact regions; and constructing the fluid saturation model from the partitioned subsurface region model.

A method and apparatus for hydrocarbon management, including generating a fluid saturation model for a subsurface region. Generating such a model may include: performing a brine flood petrophysical inversion to generate inversion results; iteratively repeating: classifying rock types (including at least one artificial rock type) based on the inversion results; generating a trial fluid saturation model based on the classified rock types; performing a trial petrophysical inversion with the trial fluid saturation model to generate trial results; and updating the inversion results with the trial results; and generating the fluid saturation model for the subsurface region based on the inversion results. The petrophysical inversion may include a facies-based inversion and/or may invert for water saturation. Generating such a model may include: performing a brine flood petrophysical inversion, performing a hydrocarbon flood petrophysical inversion; identifying misfits in the inversion results, and generating a trial fluid saturation model based on the misfits.

The harmonic wave, which is oscillation of a physical value along one direction of propagation in a homogeneous medium, is recorded by means of sensors along the direction of propagation of the oscillation at least at five points equally spaced from each other. The output signals of the sensors are converted into the corresponding complex spectral amplitudes corresponding to the frequency decomposition of the output signals. A model of harmonic wave propagation in a homogeneous medium is created, in which for any oscillation frequency the wave is represented as descending and ascending exponentially decaying harmonic waves propagating in opposite directions. The absolute values of the complex spectral amplitudes of the output signals of the sensors at each frequency are used as input data for equations comparing the absolute values of the complex amplitudes with the created model of wave propagation. By solving the obtained equations, the total complex amplitudes of the descending and ascending waves and the complex propagation constant of oscillations at each frequency are determined and the characteristics of the boundaries of the homogeneous medium are determined basing on the ratio of the complex amplitudes of the descending and ascending waves, and the characteristics of the homogeneous medium are determined basing on the phase velocity and attenuation coefficient of the wave.

A method can include receiving sample information for reservoir fluid samples and automatically selecting one or more equations of state from a plurality of different equations of state, which can suitably match the reservoir fluid samples and/or other samples. Such a method can also include automatically generating initial conditions based at least in part on sample information where such initial conditions along with one or more selected equations of state can be utilized in simulating physical phenomena using at least a reservoir model to generate simulation results. Such a method can include outputting at least a portion of the simulation results, which may be utilized in one or more processes.

Disclosed is a method for simulation of a microscopic flow of pre-crosslinked gel suspension liquid in a porous medium, including the steps of: establishing a simulation area of the porous medium based on a two-dimensional core CT slice image and subjecting the simulation area to numerical grid discretization; setting initial position and original shape of pre-crosslinked gel particles to generate virtual boundary mark points; marking the type of numeric grid nodes; calculating the force of the fluid on each virtual boundary mark point according to the momentum change of the numerical grid nodes on the boundary of the pre-crosslinked gel particles; calculating the contact force on each virtual boundary mark point using a particle contact action model; calculating the bending recovery force and the stretching recovery force for each virtual boundary mark point based on the current shape and original shape of the pre-crosslinked gel particles; and calculating the velocity and displacement of each virtual boundary mark point based on Newton's second law, wherein the respective virtual boundary mark points are connected to obtain the overall shape and position of the pre-crosslinked gel particles.

A method can include receiving n-dimensional data where n is equal at least three; analyzing a plurality of two-dimensional slices of the n-dimensional data to determine characteristic information with respect to a plurality of feature indexes for a feature in the n-dimensional data; and, based at least in part on the characteristic information, associating the feature with one of the feature indexes.

Disclosed is a method for simulation of a microscopic flow of pre-crosslinked gel suspension liquid in a porous medium, including the steps of: establishing a simulation area of the porous medium based on a two-dimensional core CT slice image and subjecting the simulation area to numerical grid discretization; setting initial position and original shape of pre-crosslinked gel particles to generate virtual boundary mark points; marking the type of numeric grid nodes; calculating the force of the fluid on each virtual boundary mark point according to the momentum change of the numerical grid nodes on the boundary of the pre-crosslinked gel particles; calculating the contact force on each virtual boundary mark point using a particle contact action model; calculating the bending recovery force and the stretching recovery force for each virtual boundary mark point based on the current shape and original shape of the pre-crosslinked gel particles; and calculating the velocity and displacement of each virtual boundary mark point based on Newton's second law, wherein the respective virtual boundary mark points are connected to obtain the overall shape and position of the pre-crosslinked gel particles.

Wavelet estimation may be performed in a reservoir simulation model that is constrained by seismic inversion data and well logs. A synthetic seismic trace is generated along with an estimated wavelet. The reservoir simulation model is revised based on results from model comparisons to actual data or base seismic data and is then used to perform a wavelet estimation. The estimated wavelet may then be used to plan further production at the well site environment, additional production at additional well site environments or any other production and drilling operation for any given present or future well site environment.

A method of generating a model for predicting at least one property of a fluid at a sample location within a hydrocarbon reservoir includes simulating behaviour of one or more hydrocarbon reservoirs during production; generating a plurality of simulated fluid samples from the one or more simulated hydrocarbon reservoirs, the plurality of simulated fluid samples corresponding to a plurality of different spatial locations and/or different time locations within the one or more simulated hydrocarbon reservoirs; generating a training data set including input data and target data based on the simulated fluid samples, the input data including simulated mud-gas data for each sample location indicative of mobile and immobile hydrocarbons at the sample location, and the target data including the at least one property of only the mobile hydrocarbons at each sample locations; and constructing a model using the training data set such that the model can be used to predict the at least one property of the fluid at a sample location based on measured mud-gas data for the sample location.