Abstract: Systems and methods for determining caprock integrity for geological sequestration of CO2, such as in above saline aquifers. The testing system for performing the method includes a core container in fluid communication with an upstream reservoir and an upstream pump, further in fluid communication with a downstream liquid reservoir and a downstream liquid pump, and further in fluid communication with a downstream gas reservoir and a downstream gas pump. The method includes determining transient hydraulic conductivity and hydraulic gradient of a caprock core sample using the testing system based on non-Darcy flow.

Abstract: A method includes performing, on a core sample obtained from a reservoir and positioned in a permeability measurement assembly that includes a flow inlet, a permeability operation by flowing a test fluid from the flow inlet and into the core sample and changing an effective stress acting on the core sample. The method also includes determining a natural logarithm of permeability of the core sample as a function of the effective stress, and determining, as a function of the natural logarithm of permeability of the core sample, an initial pore pressure of the reservoir.

Abstract: Wellbore treatment fluids are provided that include an aqueous component and an amphiphilic hyperbranched copolymer comprising the polymerized reaction product of at least a first monomer and a second monomer, where the first monomer comprises at least one surface reactive end group chosen from the group consisting of carboxylates, phosphonates, sulfonates, and zwitterions. Also provided are methods of modifying subsurface energy of a carbonate formation using the wellbore treatment fluids.

Abstract: Techniques for determining properties of a rock sample include performing a plurality of series of permeability measurements of a rock sample with a permeability test assembly to derive permeability values, where each series includes permeability measurements of the rock sample at a respective, constant differential pressure between a particular confining pressure and a particular pore pressure; for each series of the plurality of series, performing a curve fit operation to determine a slope and an intercept of a curve associated with a selected Biot coefficient, the permeability values, and the particular pore pressures to generate a plurality of slope values and a plurality of intercept values; determining an effective stress coefficient of the rock sample; and determining an actual Biot coefficient of the rock sample.

Abstract: A method includes identifying a wellbore that extends from a terranean surface and to a subterranean formation that includes a saline aquifer; injecting, through the wellbore, a predetermined volume of freshwater into a portion of the saline aquifer adjacent the wellbore to create a freshwater ring about the wellbore in the subterranean formation; and subsequent to injecting the predetermined volume of freshwater, injecting a carbon dioxide fluid, through the wellbore, and into the subterranean formation for sequestration.

Abstract: A method of analyzing a caprock of an aquifer includes determining, using a laboratory measurement device, a threshold hydraulic gradient of the caprock at which brine flows vertically in the caprock. The method further includes determining a breakthrough pressure of the caprock, wherein the breakthrough pressure reflects a difference between a CO2 pressure in the aquifer and a brine pressure in the caprock. The method further includes calculating, via a computing system that includes one or more hardware processors, an effective breakthrough pressure of the caprock based on the threshold hydraulic gradient and the breakthrough pressure, wherein the effective breakthrough pressure accounts for non-Darcy flow of the brine within the caprock.

Abstract: Apparatus and methods for determining caprock integrity. The testing apparatus for performing the method including a core container in fluid communication with an upstream reservoir and an upstream pump, and further in fluid communication with a downstream reservoir and a downstream pump. The method including determining threshold hydraulic gradient of a caprock core sample using the testing apparatus.

Abstract: A method may include obtaining reservoir data, hydraulic fracturing data, and static wellbore data for a geological region of interest. The method may further include obtaining temporal production data for the geological region of interest. The temporal production data may include a predetermined production rate with respect to a predetermined period of time. The method may further include determining various temporal features based on the temporal production data and an extraction process. The extraction process may include a deconvolution function that separates a portion of the temporal features from the predetermined production rate. The method may further include determining, using a machine-learning model, predicted hydrocarbon-in-place (HIP) data for the geological region of interest using the reservoir data, the hydraulic fracturing data, the static wellbore data, and the temporal features. The method may further include transmitting a command to a well control system based on the predicted HIP data.

Abstract: Methods and systems are disclosed. The methods may include obtaining, from a subterranean region of interest, a rock sample having a rock type and defining a sequence of pore pressure, confining stress (PPCS) pairs such that a sequence of effective stresses monotonically changes. The methods may further include determining a sequence of permeabilities by subjecting the rock sample to the sequence of PPCS pairs and determining a relationship between the sequence of PPCS pairs and the sequence of permeabilities. The methods may further still include determining a parameter using the relationship and a permeability model, where the permeability model includes the parameter and determining an in situ permeability for an in situ rock in the subterranean region of interest using, at least in part, the parameter and the permeability model, where the in situ rock is of the rock type.

Abstract: Wellbore treatment fluids are provided that include an aqueous component and an amphiphilic hyperbranched copolymer comprising the polymerized reaction product of at least a first monomer and a second monomer, where the first monomer comprises at least one surface reactive end group chosen from the group consisting of carboxylates, phosphonates, sulfonates, and zwitterions. Also provided are methods of modifying subsurface energy of a carbonate formation using the wellbore treatment fluids.

Abstract: A method and a system for predicting well production of a reservoir using machine learning models and algorithms is disclosed. The method includes obtaining a training data set for training a machine learning (ML) model and selecting an artificial neural network model structure, the model structure including a number of layers and a number of nodes of each layer. Further, the method includes generating a plurality of individually trained ML models and calculating a model performance of each trained model by evaluating a difference between a model prediction and a well performance data. The plurality of top-ranked individually trained ML models is constrained using one or multiple known physical rules. A plurality of individual predicted well production data is generated using the geological, the completion, and the petrophysical data of interest and a final predicted well production data is generating based on the plurality of individual predicted well production data.

Abstract: Methods and systems are disclosed. The methods may include determining a first sequence of permeabilities by subjecting a rock sample to a first sequence of confining stress, axial stress, pore pressure (CSASPP) triplets and determining a first rock parameter using the first sequence of permeabilities, the first sequence of CSASPP triplets, and a first permeability model. The methods may further include determining a second sequence of permeabilities by subjecting the rock sample to a second sequence of CSASPP triplets and determining a second rock parameter using the second sequence of permeabilities, the second sequence of CSASPP triplets, and the first permeability model. The method may still further include determining an in situ permeability for an in situ rock based on an initial permeability, a second stress sensitivity parameter, a first stress sensitivity parameter, a confining stress value, axial stress values, a pore pressure value, and a second permeability model.

Abstract: Systems and methods for analyzing and modeling natural gas flow in subterranean shale reservoirs. In some embodiments, methodologies and techniques for determining and modeling natural gas flow in shale formations using methodologies and techniques capable of determining natural gas properties related to dual-continuum flow, permeability, and pressure within a subterranean shale reservoir. In some embodiments, the natural gas properties are determined by subjecting a subterranean shale reservoir sample to pulse-decay analysis. In certain embodiments, the methodologies and techniques described may be used in various reservoirs exhibiting macroporosity and microporosity, such as fractured reservoirs and carbonate reservoirs composed of reservoir fluids.

Abstract: A method for determining a matrix permeability of a subsurface formation, including the steps: acquiring a core from the subsurface formation, imposing a fluid to the core until the core is saturated with the fluid, conducting a pressure-pulse decay (PD) method on an upstream and a downstream side of the core by applying a pressure-pulse on the upstream and the downstream side of the core, and determining the matrix permeability from decays of the pressure-pulses on the upstream side and downstream side, respectively.

Abstract: Systems and methods for analyzing and modeling natural gas flow in subterranean shale reservoirs. In some embodiments, methodologies and techniques for determining and modeling natural gas flow in shale formations using methodologies and techniques capable of determining natural gas properties related to dual-continuum flow, permeability, and pressure within a subterranean shale reservoir. In some embodiments, the natural gas properties are determined by subjecting a subterranean shale reservoir sample to pulse-decay analysis. In certain embodiments, the methodologies and techniques described may be used in various reservoirs exhibiting macroporosity and microporosity, such as fractured reservoirs and carbonate reservoirs composed of reservoir fluids.

Abstract: A system and methods for predicting well performance are disclosed. The method includes obtaining first geoscience data and first performance data, obtaining second geoscience data and second performance data, and obtaining new geoscience data for a new well. The method further includes training a first neural network and determining predicted second performance data using the first neural network. The method still further includes determining a residual between the second performance data and the predicted second performance data and training a second neural network. The method still further includes determining predicted new performance data for the new well by inputting a subset of the new geoscience data into the first neural network, determining a new residual for the new well by inputting the new geoscience data into the second neural network, and updating the predicted new performance data using the new residual.

Abstract: A method for determining a matrix permeability of a subsurface formation, including the steps: acquiring a core from the subsurface formation, imposing a fluid to the core until the core is saturated with the fluid, conducting a pressure-pulse decay (PD) method on an upstream and a downstream side of the core by applying a pressure-pulse on the upstream and the downstream side of the core, and determining the matrix permeability from decays of the pressure-pulses on the upstream side and downstream side, respectively.

Abstract: A method for determining maximum recoverable hydrocarbon (EMR) in a tight reservoir is disclosed. The method includes determining, based on downhole logs, a total measure of hydrocarbon amount within the tight reservoir, determining, by at least attributing fluid loss during core surfacing of the core sample to hydrocarbons, a non-recoverable measure of hydrocarbon amount within a core sample of the tight reservoir, and determining an EMR measure based on the total measure of hydrocarbon amount and the non-recoverable measure of hydrocarbon amount, wherein during the core surfacing pore pressure reduces from a reservoir condition to a surface condition.

Abstract: A method for determining SRV and EUR includes: monitoring an amount and a density of a hydrocarbon fluid produced from the production well; obtaining a cumulative amount of the fluid that has accumulated from a beginning of production; obtaining a relationship between the cumulative amount and a square root of the time; determining a deviation point where the relationship changes from linear to non-linear; determining a deviation amount of the fluid corresponding to the deviation point; determining a first density of the hydrocarbon fluid at the beginning of production, a second density at a pore pressure equal to a bottom hole pressure in the production well, a first porosity at the beginning of production, and a second porosity for a pore pressure equal to the bottom hole pressure; and determining SRV and the EUR based on the deviation amount, the first and second densities, and the first and second porosities.

Abstract: A method for predicting well production is disclosed. The method includes obtaining a training data set for a machine learning (ML) model that generates predicted well production data based on observed data of interest, generating multiple sets of initial guesses of model parameters of the ML model, using an ML algorithm applied to the training data set to generate multiple individually trained ML models based the multiple sets of initial model parameters, comparing a validation data set and respective predicted well production data of the individually trained ML models to generate a ranking, selecting top-ranked individually trained ML models based on the ranking, using the data of interest as input to the top-ranked individually trained ML models to generate a set of individual predicted well production data, and generating a final predicted well production data based on the set of individual predicted well production data.