Systems and methods include a computer-implemented method for generating a detailed heterogeneities map of a main reservoir. Pressure data for multiple wells of a main reservoir is received during a simultaneous field shut-in of the multiple wells. A scaled rate of change of pressure for each well is determined using the pressure data for each well. Rates of change of pressure for the multiple wells are plotted using the scaled rates of change of pressure. Clusters of wells having rates of change of pressure within a threshold difference of other wells in a given cluster are determined based on the plotting. A detailed heterogeneities map of the main reservoir is generated based the clusters of wells. The heterogeneities map defines heterogeneous regions. Each region contains a set of wells assigned to the heterogeneous region based on the wells having similar rates of change of pressure.

The present disclosure provides a workflow for modelling EOR flooding operations performed on a reservoir by separating front tracking from the reservoir simulation process, so that the fronts position and topology evolves in parallel with the coarse grid simulation, through modifications using machine-learning-trained correlations.

A data acquisition program, which includes core, image log, microseismic, DAS, DTS, and pressure data, is described. This program can be used in conjunction with a variety of techniques to accurately monitor and conduct well stimulation.

Provided are embodiments for hydrocarbon reservoir development that include the following: identifying proposed well locations within a reservoir boundary, for each location, developing a well plan by: (a) identifying layers of the reservoir located below the proposed location; (b) iteratively assessing the layers (from deepest to shallowest) to identify a deepest “suitable” layer that is not dry, congested, or unsuitable for gas production; and (c) performing the following for the identified layer and the location: (i) determining a borehole configuration for the location; (ii) determining a completion type for the location; and (iii) determining a stimulation treatment for the location, where a well plan for the location (e.g., for use in developing the reservoir) is generated that specifies some or all of a well location, the target layer, a borehole configuration, a completion type, and a stimulation treatment that corresponds to those determined for the proposed well location.

Methods, apparatuses, and mediums related to a full-wavefield angle gather generation for high-contrast inter-thin bed modeling for reservoir characterizations of a survey region are provided. A method may include a well logging tool having one or more sonic generators and one or more well log data recording sensors in a wellbore. Sound waves may be generated using the one or more sonic generators in order to generate reflections in the survey region. Well log data, based on the reflections, may be received using well log data recording sensors, and the well log data may be transmitted to at least one memory. A method may perform, using a computer system, a full-wavefield angle gather generation. A method may generate, by a computer system, the high-contrast inter thin-bed models based on the full-wavefield angle gather.

Hybrid seismic inversion methods and apparatuses perform wave equation inversion and stochastic inversion to generate one or more final models for the reservoir characterization of the survey region. A method may include retrieving seismic data using seismic data recording sensors; storing the seismic data in the database; retrieving well data using the well born sensor in the wellbore; storing the seismic data in the database; storing geology integration information and one or more background models in the database; retrieving the seismic data and processing the seismic data to mitigate the seismic data for a seismic hybrid inversion; and performing the seismic hybrid inversion including performing wave equation inversion and stochastic inversion to generate the one or more final models for the reservoir characterization of the survey region.

A workflow using techniques for improving signal-to-noise ratio and decreasing interferences for Low-Frequency Distributed Acoustic Sensing is described.

Systems and methods include a method for determining a breakdown pressure for the wellbore. Input parameters are received for computing a breakdown pressure for a wellbore. A pore pressure is determined using a Stehfest method equation using a function of a time duration, a distance from the wellbore, an injection fluid compressibility, a Biot poroelastic parameter, and a modified Bessel function. A poroelastic stress is determined using a poroelastic stress equation based on the pore pressure determined for the wellbore, a Composite Simpson's Rule for numerical integration, an empirical parameter, a pore pressure, a Biot poroelastic parameter, tensile strength of rock, and a Poisson distribution. A breakdown pressure is determined using a tested time-based formula, poroelastic stress, a minimum and a maximum horizontal stress, using a formula tested against multiple wells and a distance from the wellbore in a radial direction.

A global objective function is initialized to an initial value. A particular model simulation process is executed using prepared input data. A mismatch value is computed by using a local function to compare an output of the particular model simulation process to corresponding input data for the particular model simulation process. Model objects associated with the particular model simulation process are sent to another model simulation process. An optimization process is executed to predict new values for input data to reduce the computed mismatch value.

A method includes receiving a first transition probability matrix (TPM) of a subsurface region, wherein the TPM defines, for a given lithology at a current depth sample (or micro-layer), a probability of particular lithologies at a next depth sample (or micro-layer), receiving seismic data for the subsurface region, utilizing the first TPM and the seismic data to generate first pseudo wells, calculating a second TPM from the first pseudo wells, determining whether the second TPM is consistent with the first TPM, and utilizing the first pseudo wells to characterize a reservoir in the subsurface region when the second TPM is determined to be consistent with the first TPM.