Abstract: Methods and apparatus for inspecting oilfield infrastructure components. Methods include methods of identifying a micro-annulus outside a casing in a cemented wellbore. Methods may include transmitting an acoustic pulse incident on the casing; making a measurement of a first acoustic impedance property value from pulse-echo information generated responsive to an echo of the acoustic pulse reflected from the casing; propagating a circumferential guided wave in the casing; making a measurement of a second acoustic impedance property value from propagating wave information generated responsive to the propagating acoustic wave; and determining from the first acoustic impedance value and the second acoustic impedance value a presence of a micro-annulus between the casing and the cement.

Abstract: Embodiments of determining a vertically transverse isotropy (VTI) anisotropy along a horizontal section of a wellbore drilled into a formation are provided. One embodiment comprises determining elastic constants C11, C44, and C66 of the horizontal section and determining a vertical compressional slowness of the horizontal section corresponding to an elastic constant C33 of the horizontal section using a model with a condition. The model is built using second sonic log data and second density log data of the vertical wellbore. The condition is that the shear slowness (DTS) of the vertical wellbore is equal to the vertically polarized shear slowness (DTSV) of the horizontal section. The embodiment further comprises determining a VTI anisotropy along the horizontal section using the elastic constants C11, C44, C66, and C33 of the horizontal section.

Abstract: Methods for training machine learning algorithms for generation of a reservoir digital twin include receiving information obtained from hydrocarbon wells. The information includes porosity logs, petrophysical data, rock typing data, pressure transient test results, vertical production logs, reservoir pressure logs, reservoir saturation logs, production performance, and injection performance. The reservoir saturation logs are normalized in accordance with time. A machine learning algorithm is trained using the reservoir pressure logs, the production performance, and the injection performance to provide variations in reservoir pressure of the hydrocarbon reservoir in accordance with time. The machine learning algorithm is trained to provide variations in reservoir saturation of the hydrocarbon reservoir in accordance with time.

Abstract: Component weight and/or volume fractions of subterranean rock are determined. A formation model generates mineral and fluid concentration data from which elemental concentrations are calculated. Forward modeling produces a simulated energy spectrum, and simulation produces a simulated constraining log. Spectra is generated by detecting gamma radiation with a neutron logging tool, and a constraining log is generated. The spectrum and the simulated energy spectrum are compared with resultant error determined. The constraining log and simulated constraining log are compared with resultant error determined. The formation model generates further mineral and fluid concentration to calculate further elemental concentrations. Forward modeling produces further simulated energy spectrum signal and further constraining logs. The spectrum signals and further simulated spectrum signal are compared with resultant error determined.

Abstract: Systems and methods for multiscale sectors based hydrocarbon reservoir simulation that include dividing a full-field reservoir model into regions and sub-regions, and iteratively assessing and reconnecting models of the sub-regions and regions in a sequential manner to generate an adjusted full-field model.

Abstract: A computer-implemented method may include receiving test data representing a cutter/rock interaction for a cutter/rock pair; calibrating an analytical model to represent the cutter/rock interaction mechanism for a cutter/rock pair; applying the calibrated analytical model to expand the test data to form one of a plurality of expanded test datasets; generating a first neural network model, of a plurality of first neural network models, representing cutter/rock interaction between a plurality of cutters of different cutter sizes and a particular rock type, wherein the first neural network is generated using the plurality of expanded test datasets as training input; generating a second neural network model using the plurality of first neural network models as training input, wherein the second neural network model represents non-tested cutter/rock interactions between a plurality of cutters of different cutter sizes and a plurality of rock types.

Abstract: In an example method, one or more processors receive a plurality of rock fragment images. Each of the rock fragment images represents respective rock fragments obtained from a subsurface formation during well bore drilling. The one or more processors select one or more portions of the rock fragment images, and generate a geological formation image based on the one or more selected portions of the rock fragment images. The geological formation image is indicative of one or more geological characteristics of the subsurface formation along the well bore.

Abstract: A method and system for modeling a subsurface region include applying a trained machine learning network to an initial petrophysical parameter estimate to predict a geologic prior model; and performing a petrophysical inversion with the geologic prior model, geophysical data, and geophysical parameters to generate a rock type probability model and an updated petrophysical parameter estimate. Embodiments include managing hydrocarbons with the rock type probability model.

Abstract: Geologic modeling methods and systems disclosed herein employ fault face parameterization to constrain and improve the transformation of a faulted physical space geologic model into an unfaulted depositional space geologic model. An illustrative embodiment includes: associating a seismic image with each face of at least one fault in a subsurface region; determining a correspondence map between the seismic images for said at least one fault; parameterizing the faces using the correspondence map to match parameter value assignments for corresponding portions of the faces; creating a displacement map that draws together matching parameter values to align the corresponding portions of the faces; applying the displacement map to the geologic model to create a design space model; modifying the design space model; applying the displacement map in reverse to the modified design space model to obtain a modified geologic model; and outputting the modified geologic model.

Abstract: The invention discloses a mechanics calculation method of drill bit tooth considering rock dynamic strength and mixed crushing mode, including: Step S1: selecting a target drill bit tooth and a target rock, and determining a type of target drill bit tooth, a geometry of the target drill bit tooth, a rock type and rock parameters of the target rock; Step S2: calculating a horizontal cutting force of the target drill bit tooth according to a horizontal cutting mechanics calculation method of drill bit tooth; Step S3: calculating a vertical penetration force of the target drill bit tooth according to a vertical penetration mechanics calculation method of drill bit tooth; Step S4: calculating a resultant force experienced by the target drill bit tooth according to a resultant force calculation method of drill bit tooth. The invention provides a calculation method for accurately obtaining drill bit tooth mechanics under different working conditions.

Abstract: 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. The model includes a shore line and a fluvial formation connected to the shore line at a point of the model. The shore line divides the model into a marine zone and a continental zone. The method further includes determining a delta zone in the model based on the shore line and based on the fluvial formation, determining a stochastic trajectory in said delta zone, and determining a lobe formation in said delta zone based on the determined stochastic trajectory based on a stochastic process.

Abstract: The invention discloses a method for improving a recovery ratio of a braided well pattern of a hugely thick or multi-layer oil and gas reservoir, which improves the recovery ratio of the hugely thick or multi-layer oil and gas reservoir by designing the braided well pattern. The braided well pattern is designed through the following method: dividing a cubic development unit of the oil and gas reservoir; measuring a physical property parameter of the cubic development unit; calculating a well pattern design parameter according to the physical property parameter, wherein the well pattern design parameter includes a number of wells and a well bore track; and drilling a large-displacement horizontal well according to the well pattern design parameter.

Abstract: A method, article and system are provided for processing and interpreting acoustic data. The method and system includes providing a number of acoustic processing elements, each element being associated with an acoustic mode of a number of acoustic modes of a sonic measurement tool adapted to acquire data representing acoustic measurements in a borehole. In addition the method and system includes providing a user interface to organize a processing chain of the number of acoustic processing elements such that the acoustic processing elements process the acquired data according to a predefined workflow.

Abstract: Geomechanical parameters can be used to optimize a well configuration that includes one or more projected wells having locations and geometries. Formation data and regional stress information of a formation can be used to determine a local stress variation of the formation. A quality index can be generated by combining petrophysical properties with the local stress variation. Hydrocarbon recovery flow simulations can be generated by generating well configuration models based on the quality index, generating reservoir geomechanical model that includes hydraulic fracture propagation characteristics, determining new hydraulic fractures by simulating propagation through the reservoir geomechanical model and using geomechanical rules, and determining a projected hydrocarbon recovery rate by simulating flow with the new hydraulic fractures. A well placement plan can be selected using the projected hydrocarbon recovery rates. The well placement plan can be output to be used to plan one or more wellbores.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, by a neural network (NN), a dataset for generating features from the dataset. A first set of features is computed from the dataset using at least a feature layer of the NN. The first set of features i) is characterized by a measure of informativeness; and ii) is computed such that a size of the first set of features is compressible into a second set of features that is smaller in size than the first set of features and that has a same measure of informativeness as the measure of informativeness of the first set of features. The second set of features if generated from the first set of features using a compression method that compresses the first set of features to generate the second set of features.

Abstract: Embodiments of generating a self-consistent earth model are provided. One embodiment comprises: a) building a structured geologic; b) generating a mineralogy volume; c) generating a porosity volume and a density volume; d) generating a pressure volume; e) generating a geophysical property volume comprising a P-wave velocity volume and a S-wave velocity volume, a relationship between P-wave velocity and S-wave velocity, or any combination thereof; f) generating mechanical elastic properties based on (i) a static to dynamic elastic property relationship and (ii) the geophysical property volume, the relationship between P-wave velocity and S-wave velocity, or any combination thereof; and g) performing mechanical earth modeling using the mechanical elastic properties, the density volume, and the pressure volume to generate a self-consistent earth model.

Abstract: A three-dimensional grid of a hydrocarbon reservoir can be received. The three-dimensional grid can include a plurality of cells, each cell of the plurality of cells can include a first index value, a second index value, and a third index value. The first index value, the second index value, and the third index value of each cell can together uniquely identify each cell of the plurality of cells. Each cell can further include at least one parameter measured from the hydrocarbon reservoir. A hydrocarbon saturation distribution of the hydrocarbon reservoir can be determined using a saturation height function and the at least one parameter of each cell of the plurality of cells. The hydrocarbon saturation distribution can include a cell hydrocarbon saturation estimate for each cell of the plurality of cells. The hydrocarbon saturation distribution can be provided. Related apparatus, systems, techniques and articles are also described.

Abstract: A test tool attached to test string comprising a fluid conduit is deployed to a test position within a wellbore. The deployment includes hydraulically isolating a portion of the wellbore proximate the test tool to form an isolation zone containing the test position. A fluid inflow test is performed within the isolation zone and an initial formation property and a fluid property are determined based on the fluid inflow test. A fluid injection test is performed within the isolation zone including applying an injection fluid through the test string into the isolation zone, wherein the flow rate or pressure of the injection fluid application is determined based, at least in part, on the at least one of the formation property and fluid property.

Abstract: 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.

Abstract: A method for estimating a probability of a drilling dysfunction or a drilling performance indicator value occurring includes entering drilling-related data having a probability distribution into a mathematical model of a drill string drilling a borehole penetrating the earth and entering drilling parameters into the model for drilling the borehole. The method further includes performing a plurality of drilling simulations using the model, each simulation providing a probability of the drilling dysfunction occurring or a probability of a drilling performance indicator value occurring with associated drilling parameters used in the simulation, selecting a set of drilling parameters that optimizes a drilling objective using the probabilities of the drilling dysfunction occurring or the probabilities of a drilling performance indicator value occurring; and transmitting the selected set of drilling parameters to a signal receiving device.

Abstract: Methods are provided for adaptive optimization of enhanced oil recovery project performance under uncertainty. Predictive physics-based reservoir simulation is used to estimate performance of the project. Input parameters of the model are divided into control variables and uncertain variables. The reservoir model is optimized to obtain values of control variables maximizing mean value of a chosen performance metric under initial uncertainty of formation and fluid properties. An efficient frontier can characterize dependence between the optimized mean value of the performance metric and its uncertainty expressed by the standard deviation. Global sensitivity analysis (GSA) is then applied to quantify and rank contributions from uncertain input parameters to the standard deviation of the optimized values of the performance metric. Additional measurements can be performed to reduce uncertainty in the high-ranking parameters.

Abstract: A method includes obtaining a reservoir model for a subsurface reservoir, identifying a current state of the subsurface reservoir using the reservoir model, and a computer processor selecting an optimization function from multiple optimization functions according to the current state of the reservoir to obtain a selected optimization function. The method further includes the computer processor calculating valve positions of physical devices using the selected optimization function. The valve positions are implemented.

Abstract: Techniques for determining one or more hydrocarbon sweet spots include generating a three-dimensional (3D) simulation model of a hydrocarbon reservoir in a subterranean formation; executing a gas winnowing process to the 3D simulation model; applying one or more geomechanical restraints to the 3D simulation model; activating one or more energy simulation parameters with the 3D simulation model; applying a total dynamic productivity index (TDPI) process to the 3D simulation model to generate at least one 3D index that includes one or more hydrocarbon sweet spots; and generating a graphical representation of the generated 3D index for presentation on a graphical user interface (GUI) to a user.

Abstract: Techniques for predicting a landing zone of a wellbore include identifying a first subsurface geological model of a first subterranean layer located under a terranean surface that includes an upper boundary depth of the first subterranean layer and a lower boundary depth of the first subterranean layer; identifying a second subsurface geological model of a second subterranean layer deeper than the first subterranean layer that is independent of the first subsurface geological model and includes an upper boundary depth of the second subterranean layer; correlating a predicted landing zone for a plurality of wellbores using the first and second subsurface geological models that is based on a location of a horizontal portion of each wellbore; and generating data that comprises a representation of the correlated plurality of wellbores for presentation on a graphical user interface (GUI).

Abstract: Well management includes receiving, from a user computing system, a simulation job request for simulating well management on the cloud computing system including compute nodes, and obtaining, for the simulation job request, search spaces for completion stage simulations, fracture stage simulations, and production stage simulations. Well management further includes orchestrating, using the search spaces, the completion stage simulations, the fracture stage simulations, and the production stage simulations on the cloud computing system to obtain at least one optional well plan, and sending the at least one optional well plan to the user computer system.

Abstract: A self-adapting digital twin of a wellbore environment can be created. The self-adapting digital twin incorporates a standalone Ensemble Kalman Filter (EnKF) module with a constant parameter digital twin developed for a fixed environment. The standalone EnKF module receives streaming measurement data from multiple sensors and prediction data from the digital twin and executes the standalone EnKF module using the streaming measurement data and the prediction data from the digital twin. The results of executing the standalone EnKF module are input parameter corrections for the digital twin that are communicated to the digital twin. Output predictions of the digital twin are used to modify operational parameters of an oil or gas recovery process.

Abstract: Disclosed is a compressor system suitable for carrying out artificial gas lift operations at an oil or gas well. Also disclosed is a method for controlling the compressor system. The methods disclosed provide the well operator with the ability to identify and maintain gas injection rates which result in the minimum production pressure. The minimum production pressure will be determined either by a bottom hole sensor or a casing pressure sensor located at the surface or any convenient location capable of monitoring pressure at the wellhead.

Abstract: A system for analysis and display of hydrocarbon play information according to some aspects determines a probability of source rock occurrence according to source rock age based on a proven play concept. The system can also determine a relative probability of migration for hydrocarbons from a source rock of a proposed petroleum play concept to a reservoir. A relative probability of wellbore success for the proposed play concept can be determined at least in part based on these probabilities. The system can display the relative probability of wellbore success for the proposed play concept, either alone as part of a displayed inventory of proposed hydrocarbon play concepts. The system can produce accurate results that facilitate rapid play concept investigations for hydrocarbon exploration.

Abstract: Techniques for determining a spacing, such as one or more distances, between two or more wellbores formed from a terranean surface to a subterranean formation are described. In some aspects, a wellbore segment is determined for both a first and a second wellbore. One or more distances between the wellbore segments on the first and second wellbores, respectively, is determined. From the determined distance between the wellbore segments on the first and second wellbores, one or more distances between the first and second wellbores may be determined.

Abstract: The disclosure presents a technique for determining how downhole material will be distributed among two or more active perforation clusters in a hydraulic fracturing well system. The determination can be conducted during the execution of a treatment stage allowing modifications prior to completion of the treatment stage. The technique utilizes a three-step process where a first step can determine a predictive model of the wellbore, such as subterranean formation properties, wellbore properties, and target goal of the treatment stage. A second step can calibrate for unknown parameters, such as downhole HF fluid pressure at the active perforation clusters and downhole HF fluid flow rate at the perforation clusters. A third step can predict how downhole material will be distributed to the active perforation clusters and fracture clusters. The prediction result can be utilized to modify a pumping plan of the treatment stage to better achieve the targeted goal.

Abstract: A method for training a predictive reservoir simulation in which high-confidence reservoir sample data is used to identify misallocated historical production data used in the simulation. A neural network algorithm is trained with high-confidence reservoir historical production data. High-confidence reservoir sample data is obtained by at least one sensor at a reservoir location over a time interval, after which the reservoir historical production data is parametrically varied over the time interval to determine a time-indexed discrepancy between the reservoir historical production data and the high-confidence reservoir sample data over the time interval. The time-indexed discrepancy and a defined threshold discrepancy are then used as inputs to a machine learning process to further train the neural network algorithm to identify reservoir historical production data whose discrepancy exceeds the threshold discrepancy and thereby constitutes misallocated historical production data.

Abstract: An operation plan creation device includes: an operation information creation unit configured to receive an input of a simple setting including information with which an operation period of a device is identifiable and to create operation information including an inspection period and a replacement scheduled component in the operation period of the device; a component information acquisition unit configured to acquire component information including lifespan information and stock quantity information about each of the components, based on use history information about each of the plurality of components; a dummy information creation unit configured to create, when the acquired component information includes missing information, dummy information to be used instead of the missing information; and a plan creation unit configured to create the operation plan for the components related to the device based on the operation information and the component information or the dummy information.

Abstract: Techniques for determining a wellbore drilling path includes identifying input seismic data associated with a subterranean zone that includes a wellbore drilling target. The input seismic data includes primary seismic events and multiple seismic events. The input seismic data is processed to remove the multiple seismic events and at least one of the primary seismic events from the input seismic data. An orthogonalization of the processed input seismic data is performed to recover the at least one primary seismic event into a seismic image of the subterranean zone that excludes at least a portion of the multiple seismic events. A wellbore path is determined from a terranean surface toward the wellbore drilling target for a drilling geo-steering system based on the seismic image of the subterranean zone.

Abstract: A method of operating a reservoir simulator can include performing a time step of a reservoir simulation using a spatial reservoir model that represents a subterranean environment that includes a reservoir to generate simulation results for a first time where the simulation results include a front defined by at least in part by a gradient at a position between portions of the spatial reservoir model; predicting a position of the front for a subsequent time step for a corresponding second time using a trained machine model; discretizing the spatial reservoir model locally at the predicted position of the front to generate a locally discretized version of the spatial reservoir model; and performing a time step of the reservoir simulation using the locally discretized version of the spatial reservoir model to generate simulation results for the second time.

Abstract: A plant management system includes: a control device; and a management device. The control device includes: a manipulation parameter setting unit that sets values of manipulation parameters; a state parameter acquisition unit that acquires values of state parameters indicating an operating condition of the plant; and a transmitter that transmits these values to the management device. The management device includes: an acquisition unit that acquires these values; a database that stores set values of manipulation parameters and actually measured values or predicted values of state parameters when the plant is operated based on the set values, corresponding to each other; and a determination unit that determines a set value of a manipulation parameter capable of improving a value of a predetermined state parameter of the plant by referring to these values and the database.

Abstract: Systems, methods, and computer readable media for the determination of hydrogen sulfide (H2S) concentration and distribution in carbonate reservoirs using a mechanical earth model. Hydrogen sulfide (H2S) concentration in a carbonate reservoir n may be measured and correlated with horizontal maximum stresses of stress ratios determined using mechanical earth model for a strike-slip fault regime. The hydrogen sulfide (H2S) concentration at different depths in the carbonate reservoir may be determined using the correlation.

Abstract: A method for determining a slips status during a drilling operation of a subterranean formation. The method includes capturing, using one or multiple camera devices mounted on a drilling rig of the drilling operation, a plurality of images, each of the plurality of images comprising a portion that corresponds to a slips device of the drilling rig, generating, using a sensor device of the drilling rig, a plurality of parameters of the drilling rig, wherein the plurality of parameters are synchronized with the plurality of images, providing, by a computer processor, the plurality of parameters as input to a machine learning model of the drilling rig, and analyzing, by the computer processor and based on the machine learning model, the plurality of images to generate the slips status.

Abstract: A method, apparatus and system is provided for assessing risk for well completion, comprising: obtaining, using an input interface, a Below Rotary Table hours and a plurality of well-field parameters for one or more planned runs, determining, using at least one processor, one or more non-productive time values that correspond to the one or more planned runs based upon the well-field parameters, developing, using at least one processor, a non-productive time distribution and a Below Rotary Table distribution via one or more Monte Carlo trials; and outputting, using a graphic display, a risk transfer model results based on a total BRT hours from the Below Rotary Table and the non-productive time distribution produced from the one or more Monte Carlo trials.

Abstract: A system, computer-readable medium, and method for determining a potential drilling location, of which the method includes obtaining data representing a subterranean domain. The data includes at least seismic data. The method also includes inverting the seismic data, creating a petroleum systems model of the subterranean domain based at least in part on a result of inverting the seismic data, simulating a dynamic reservoir model of the subterranean domain based at least in part on the petroleum systems model, and identifying the potential drilling location based on a combination of the inverting of the seismic data, creating the petroleum systems model, and simulating the dynamic reservoir model.

Abstract: A method, system and device for comprehensively characterizing a lower limit of oil accumulation of a deep marine carbonate reservoir is provided, aiming to solve the problem that the prior art cannot: accurately determine the lower limit of oil accumulation of the deep marine carbonate reservoir, which leads to the difficulty in predicting and identifying deep effective reservoirs. The method includes: determining lower limit porosity and permeability for oil accumulation based on a boundary line; determining lower limit porosity and permeability for oil accumulation based on a movable oil ratio of a core sample; determining a lower limit pore throat radius for oil accumulation based on a mercury injection experiment; and comprehensively characterizing the lower limit of oil accumulation of a deep marine carbonate reservoir to be predicted. The method, system and device can predict and identify deep effective reservoirs.

Abstract: Fluid flow dynamics modeling methods and system are provided. In some embodiments, such methods include determining a bottomhole pressure for the unconventional reservoir based, at least in part, on a tubing head pressure for one or more wells penetrating at least a portion of the unconventional reservoir, one or more fluid properties of a fluid in the unconventional reservoir, and a well production volume for the one or more wells; determining a Productivity Index (PI) for the unconventional reservoir, based, at least in part, on the one or more fluid properties and measured well data for the one or more wells, wherein the measured well data includes a well production rate and a well flowing pressure; and determining a fluid depletion of the unconventional reservoir based, at least in part, on the bottomhole pressure and the PI.

Abstract: Disclosed are methods, systems, and computer-readable medium to perform operations including: capturing, using an image sensor directed at a drilling system, an image feed of movement of a component of the drilling system with respect to a vertical reference line; converting the image feed into a digital representation of the movement of the component, the digital representation including a number of offset pixels from the component to the vertical reference line in the image feed; converting the digital representation into a machine learning (ML), the ML representation including a plurality of vectors each including the number of offset pixels from the component to the vertical reference line at a respective time; training a ML model using the ML representation to characterize the movement of the component as normal or abnormal; and using the trained ML model to characterize the movement of the component in real-time as normal or abnormal.

Abstract: A method for improved prediction and enhancement of hydrocarbon recovery from ultra-tight/unconventional reservoirs for both the primary production and any subsequent solvent huff‘n’puff periods based on facilitating the diffusion process may include steps of defining one or more initial properties of a reservoir and integrating characterization data of the reservoir; defining a wellbore trajectory for each of at least one well and one or more parameters associated with a completion/reservoir stimulation design; specifying operating conditions for a current development cycle; performing diffusion-based dynamic fracture/reservoir simulation for calculating hydrocarbon recovery and efficiency of a hydrocarbon process; and; determining whether to commence or continue enhanced oil recovery (EOR) or enhanced gas recovery (EGR) cycles.

Abstract: Systems and methods are disclosed for generating subsurface feature prediction probability distributions from a subsurface feature as a function of position in a subsurface volume of interest. For example, a computer-implemented method may include: obtaining subsurface data and well data, generating subsurface feature values, generating subsurface feature realizations, generating subsurface feature realization uncertainty values, generating subsurface parameter values, generating subsurface parameter realizations, generating subsurface feature prediction probability distributions, generating a first representation of likelihoods of the subsurface feature values, and displaying the first representation.

Abstract: One or more methods for validating reservoir simulation models. At least one of the methods include determining one or more time segments of fluid recovery of a reservoir by analyzing a production history of the reservoir; running a simulation model, for the first time segment, to generate one or more drainage volumes; generating, for a first time segment, a plurality of grid regions along one or more no-flow boundaries of the one or more drainage volumes; generating, for the first time segment, a plurality of sector models corresponding to the plurality of grid regions; and performing, for the first time segment, a history matching process corresponding to a time phase simultaneously on each of the plurality of sector models to generate, for each of the sector models, a history matching output.

Abstract: Methods for validating reservoir simulation models can include determining one or more time segments of fluid recovery of a reservoir; generating, for a first time segment, one or more streamlines on a full simulation grid corresponding to the reservoir by performing one or more reservoir simulations; generating, for the first time segment, one or more drainage volumes; generating, for the first time segment, grid regions along one or more no-flow boundaries of the one or more drainage volumes; generating, for the first time segment, sector models corresponding to the grid regions; performing, for the first time segment, a history matching process corresponding to a time phase simultaneously on each of the sector models to generate, for each sector model, a history matching output; and comparing, for the first time segment and for each sector model, the history matching output for that sector model to a tolerance threshold.

Abstract: Fluid flow dynamics modeling methods and system are provided. In some embodiments, such methods include providing an initial fluid system model including a plurality of nodes, each node characterized by one or more node fluid system parameters; and a plurality of edges between two of the plurality of nodes, each edge characterized by one or more edge fluid system parameters; and using the initial fluid system model, determining an updated fluid system model using a history-matching process.

Abstract: Methods and systems, including computer programs encoded on a computer storage medium can be used for identifying primary-wave (P-wave) and secondary-wave (S-wave) characteristics of an underground formation by separating P-wave and S-wave modes of seismic data generated by applying a seismic source to a subterranean region of a geological area. Particle motion vectors of a P-wave are parallel to a propagation vector of the P-wave, whereas particle motion vectors of an S-wave are perpendicular to a propagation vector of the S-wave. The parallel and perpendicular relationship between the motion and propagation vectors of the respective P- and S-waves provide a basis for separating P- and S-wave components from a wavefield. The separation methodology extracts P-wave components and S-wave components from the wavefield based on an estimated angle between propagation vectors and wave motion vectors for the wavefield.

Abstract: The present disclosure pertains to a system that may be configured to operate a power grid, including generation participants, consumers, and a controller that administers a market for the power generation participants and the consumers on the power grid. The operation of the power grid may include: performing power grid coordination calculations based upon, at least in part, constraints that pertain to the flow and/or congestion of power on the grid; and managing the coordination calculations by reducing a number of constraints used in the coordination calculations, the managing including a first step of coarse screening of the constraints, a second step of deterministic fine screening of the constraints, and a third step of statistical fine screening of the constraints. This second step may cause identification of constraints that are redundant and/or dominated by other constraints.

Abstract: Systems and methods include a method for generating a high-resolution advanced three-dimensional (3D) transient model that models multiple wells by integrating pressure transient data into a static geological model. A crude 3D model is generated from a full-field geological model that models production for multiple wells in an area. A functional 3D model is generated from the crude 3D model. An intermediate 3D model is generated by calibrating the functional 3D model with single-well data. An advanced 3D transient model is generated by calibrating multi-well data in the functional 3D model.