Abstract: A method for formation properties prediction in near-real time may include obtaining lab measurements of existing drill cuttings at a plurality of depths of a first well. The method may include obtaining historical drilling surface data at the plurality of depths from a plurality of wells. The method may include obtaining real-time digital photos and real-time drilling surface data of new drill cuttings at a new depth of a new well. The method may include generating, using a prediction model, predicted formation properties of the new drill cuttings based on the real-time digital photos, the real-time drilling surface data, and the new depth. The method may include predicting, using a near-real-time model and the predicted formation properties, near-real-time formation properties in the new well, wherein the prediction model comprises a historical model that employs a machine-learning algorithm.

Abstract: An example system may be used to automate one or more processes relating to drill cutting handling, cleaning, and packing to produce consistently high-quality cleaned samples. In some implementations, an example system may employ cleaning processes including centrifugal and ultrasonic processes to clean a sample automatically without the aid of a human operator thereby increasing efficiency and quality of the produced samples for better subsequent sample analysis. A system may include an unloading module, a cleaning module, and packing module, all of which may be operated in combination with a robotic arm.

Abstract: A modular geologic core examination table is claimed. The modular geologic core examination table includes at least two legs, each leg comprising an extending portion for increasing the effective length of each leg, the extending portion at least partially concentrically disposed within or around the leg from which it extends, and wheels affixed to each of the at least two legs, wherein the wheels comprise braking functionality. The modular geologic core examination table also includes a tabletop coupled to the at least two legs, the tabletop including a top surface for receiving a core sample tray configured to hold the geologic core samples, wherein the tabletop is disposed above an automated guided vehicle (AGV) configured to navigate the modular core examination table while carrying geologic core samples from one geologic processing station to another without collisions.

Abstract: A geologic core inspection table includes at least two legs, each including an extending portion for increasing the effective length of each leg, the extending portion at least partially concentrically disposed within or about the leg from which it extends; and a tabletop disposed above and coupled to the legs. The tabletop includes a top surface for receiving a core sample tray. At least one leg may be extended to a different height than at least one other leg.

Abstract: An example system may be used to automate one or more processes relating to drill cutting handling, cleaning, and packing to produce consistently high-quality cleaned samples. In some implementations, an example system may employ cleaning processes including centrifugal and ultrasonic processes to clean a sample automatically without the aid of a human operator thereby increasing efficiency and quality of the produced samples for better subsequent sample analysis. A system may include an unloading module, a cleaning module, and packing module, all of which may be operated in combination with a robotic arm.

Abstract: A method for formation properties prediction in near-real time. The method may include obtaining lab measurements of existing drill cuttings at a plurality of depths of a first well. The method may include obtaining historical drilling surface data at the plurality of depths from a plurality of wells. The method may include obtaining real-time digital photos and real-time drilling surface data of new drill cuttings at a new depth of a new well. The method may include generating, using a prediction model, predicted formation properties of the new drill cuttings based on the real-time digital photos, the real-time drilling surface data, and the new depth. The method may include predicting, using a near-real-time model and the predicted formation properties, near-real-time formation properties in the new well, wherein the prediction model comprises a historical model that employs a machine-learning algorithm.

Abstract: Implementations of the present disclosure provide techniques for stochastic stratigraphic correlation that produce quantitative estimation of uncertainty by generating multiple viable correlations. In contrast to deterministic models where the output of the model is fully determined by the parameter values and the initial conditions, stochastic models possess some inherent randomness. Using stochastic models, the same set of parameter values and initial conditions will lead to an ensemble of different outputs. The described techniques include introducing probabilistic sampling into dynamic time warping processes. In some implementations, the techniques allow for a user to interactively update correlation markers and their associated uncertainties. The techniques can adhere to these markers and produce multiple viable solutions.

Abstract: Systems and methods for stochastic correlation of stratigraphic data in a subsurface formation include: receiving data representing stratigraphy of the subsurface formation at a plurality of locations; generating a cumulative distance matrix of the data representing the stratigraphy of the subsurface at a first location of the plurality of locations and the data representing the stratigraphy of the subsurface at a second location of the plurality of locations; obtaining, by traversing the cumulative distance matrix according to a series of deterministic steps and intermittent stochastic steps, a minimal cost path over the cumulative distance matrix; and defining, based on the performing, one or more correlations of the stratigraphy of the subsurface formation at the first location and the stratigraphy of the subsurface formation at the second location; and

Abstract: A geologic core inspection table includes at least two legs, each including an extending portion for increasing the effective length of each leg, the extending portion at least partially concentrically disposed within or about the leg from which it extends; and a tabletop disposed above and coupled to the legs. The tabletop includes a top surface for receiving a core sample tray. At least one leg may be extended to a different height than at least one other leg.

Abstract: Continuous capillary pressure (Pc) curves of subsurface rock formations adjacent wells are determined based on translation relaxation time (T2) data from nuclear magnetic resonance (NMR) and from wireline well logs, such as resistivity logs, to obtain water saturation (Sw) of the rock in the formations. The T2 data and the hydrocarbon density, water density, free water level, and paleo-water level of the formation are processed to obtain parameters of Thomeer hyperbolas that closely conform to water saturation values obtained from the other well logs. The Thomeer hyperbolas so determined are converted to capillary pressure curves.

Abstract: This subject disclosure describes methods to build and/or enhance 3D digital models of porous media by combining high- and low-resolution data to capture large and small pores in single models. High-resolution data includes laser scanning fluorescence microscopy (LSFM), nano computed tomography (CT) scans, and focused ion beam-scanning electron microscopy (FIB-SEM). Low-resolution data includes conventional CT scans, micro computed tomography scans, and synchrotron computed tomography scans.

Abstract: This disclosed subject matter is generally related to methods for characterizing two-dimensional (2D) and three-dimensional (3D) samples to determine pore-body and pore-throat size distributions and capillary pressure curves in porous media using petrographic image analysis. Input includes high-resolution petrographic images and laboratory-derived porosity measurements. Output includes: (1) pore-body and pore-throat size distributions, and (2) simulated capillary pressure curves for both pore bodies and pore throats.

Abstract: Provided are methods, systems, and computer-readable media for determining capillary pressure in a basin/reservoir. Well log data is obtained that includes permeability log data, porosity log data, water saturation log data, and oil saturation log data. Thomeer parameters for a multi-pore system of a Thomeer model are determined by evaluating an objective function that measures the mismatch between the well log data and modeled data having the Thomeer parameters as input. The objective function is iteratively evaluated using linear equality constraints, linear inequality constraints, and nonlinear equality constraints until convergence criteria are met.

Abstract: Continuous capillary pressure (Pc) curves of subsurface rock formations adjacent wells are determined based on translation relaxation time (T2) data from nuclear magnetic resonance (NMR) and from wireline well logs, such as resistivity logs, to obtain water saturation (Sw) of the rock in the formations. The T2 data and the hydrocarbon density, water density, free water level, and paleo-water level of the formation are processed to obtain parameters of Thomeer hyperbolas that closely conform to water saturation values obtained from the other well logs. The Thomeer hyperbolas so determined are converted to capillary pressure curves.

Abstract: This subject disclosure describes methods to build and/or enhance 3D digital models of porous media by combining high- and low-resolution data to capture large and small pores in single models. High-resolution data includes laser scanning fluorescence microscopy (LSFM), nano computed tomography (CT) scans, and focused ion beam-scanning electron microscopy (FIB-SEM). Low-resolution data includes conventional CT scans, micro computed tomography scans, and synchrotron computed tomography scans.

Abstract: The subject disclosure relates to methods for determining representative element areas and volumes in porous media. Representative element area (REA) is the smallest area that can be modeled to yield consistent results, within acceptable limits of variance of the modeled property. Porosity and permeability are examples of such properties. In 3D, the appropriate term is representative element volume (REV). REV is the smallest volume of a porous media that is representative of the measured parameter.

Abstract: This disclosed subject matter is generally related to methods for characterizing two-dimensional (2D) and three-dimensional (3D) samples to determine pore-body and pore-throat size distributions and capillary pressure curves in porous media using petrographic image analysis. Input includes high-resolution petrographic images and laboratory-derived porosity measurements. Output includes: (1) pore-body and pore-throat size distributions, and (2) simulated capillary pressure curves for both pore bodies and pore throats.