A reservoir model for values of a formation property is simulated using a turning bands method with distributed computing. A distributed computing system simulates the reservoir on separate machines in parallel in several stages. First, line distributions are simulated independently on turning bands. The reservoir model is partitioned into tiles and unconditional simulations are run on each tile in parallel using the corresponding simulated turning bands. The unconditional simulations within each tile are conditioned on known formation values to generate conditional simulations. Conditional simulations are aggregated across tiles to create the simulated reservoir model.

The disclosure presents processes for updating a prediction for the basin model and compaction model for a borehole. The results of the predicted parameters can be utilized by a drilling controller to adjust a drilling process, such as rotational speed, drilling fluid composition, drilling fluid additives, and other drilling process parameters. The predictions can be updated at various time intervals, such as real-time or near real-time for data collected by downhole sensors and a different time interval for sensor data collected at a lag time, such as cuttings analyzed by surface sensors. Throughout a drilling stage, the drilling process can be updated as new sensor data is received, allowing the uncertainty of the predictions to be reduced as new data is incorporated into the basin and compaction models, thereby enabling an increase in efficiency and optimization of the drilling process.

Method for characterizing subterranean formation is described. One method involves injecting a fluid into an active well of the subterranean formation at a pressure sufficient to induce one or more hydraulic fractures. Measuring, via a pressure sensor, a poroelastic pressure response caused by inducing of the one or more hydraulic fractures. The pressure sensor is in at least partial hydraulic isolation with the one or more hydraulic fractures.

Systems and methods include a computer-implemented method for predicting fluid holdups along the borehole or the pipe on surface and to perform fluid typing and fluid properties characterization. Acoustic waves are transmitted by an array of acoustic wave transducers. Each transducer is configured to transmit acoustic waves at a different frequency. The acoustic waves are received by an array of acoustic wave receivers fixed on the bow centralizer on the tool used in the borehole. Each receiver is configured to receive only the given frequency of a given transducer, forming a receiver-transducer pair for the given frequency. Acoustic speeds measured at each given frequency and analyzed. A model is generated based on the analyzing. The model is configured to predict fluid holdups across the borehole and to perform fluid typing and fluid properties characterization in one phase, two phase, and three phase applications of gas, oil, and water.

The present disclosure describes a computer-implemented method that includes: receiving a seismic dataset of a surveyed subsurface of a reservoir, the seismic dataset comprising observed pressure and production data of the reservoir as well as a set of geological and geo-mechanical parameters representing physical features of the surveyed subsurface; generating multiple realizations of a discrete fracture network (DFN) based on a subset of the set of geological and geo-mechanical parameters; selecting, from the multiple realizations, one or more realizations based on a parameter with a value under a 10% quantile of a full range of likely values; performing a forward simulation for the reservoir based on the selected one or more realizations and the observed pressure and production data; determining that a misfit of the forward simulation is below a threshold based on evaluating an objective function; and producing a model of the reservoir based on the forward simulation.

A method may include determining an energy factor based on scratch test data and ultrasonic wave data regarding a geological region of interest. The method may further include determining an amount of inelastic energy regarding the geological region of interest using triaxial compression data and rock property data. The method may further include determining a tensile strength regarding the geological region of interest using Brazilian test data. The method may further include generating a geomechanical model regarding the geological region of interest using the energy factor and the amount of inelastic energy. The geomechanical model may include various brittleness values for the geological region of interest. The method may further include determining an injection fluid pressure to induce a hydraulic fracture at a predetermined location in the geological region of interest using the geomechanical model, the tensile strength, and fracture plane roughness data.

A method may include obtaining a selection of various user-defined coarsening parameters. The user-defined coarsening parameters may include a predetermined fine-grid region in a geological region of interest and a predetermined cell distance. The method may further include determining an area of interest (AOI) mask for the geological region of interest based on the predetermined fine-grid region. The method may further include determining a geological property mask based on the user-defined coarsening parameters. The geological property mask may correspond to a predetermined geological feature within the predetermined cell distance from the AOI mask. The method may further include generating a coarsened grid model using grid model data and well data for the geological region of interest. The method may further include performing a reservoir simulation of the geological region of interest using the coarsened grid model.

2D slices/images may be extracted from a three-dimensional volume of subsurface data. Image comparison analysis across sequential 2D slices/images may identify boundaries within the corresponding subsurface region, such as changes in style of deposition or reservoir property distribution. Identification of temporal/spatial boundaries in the subsurface region where subsurface properties change may facilitate greater understanding of the scales and controls on heterogeneity, and connectivity between different locations.

Techniques for controlling a hydrocarbon production system include determining a first estimate of a prior FVC detectability probability map based on a plurality of reservoir data that includes four-dimensional (4D) seismic data of a subterranean reservoir; determining a second estimate of the prior FVC detectability probability map under seismic data noise conditions; determining an updated detectable FVC probability based on the 4D seismic data; determining an updated FVC probability based on the updated detectable FVC probability and the first and second estimates of the prior FVC detectability probability maps; and generating a control instruction for at least one of a fluid injection system or a hydrocarbon production assembly based on the updated FVC probability.

Systems and methods include a computer-implemented method for generating and using a graph/document structure to store reservoir simulation results. A graph is generated that represents reservoir simulation results of a reservoir simulation performed on a reservoir using a reservoir simulation model. The graph represents a full set of relational data and non-relational data included in the reservoir simulation results. The graph stores graph information and relational data in a graph/document structure. Objects of the reservoir, elements of the reservoir simulation results, and inputs of the reservoir simulation model are represented as vertices in the graph. Relationships between vertices are represented as edges in the graph. An edge is defined by a pair of vertices in the graph.