Abstract: A method for predicting fluid properties includes measuring one or more measured fluid properties of a mud gas at a surface of a wellbore. The method also includes measuring one or more mud gas properties of the mud gas at the surface of the wellbore. The method also includes predicting one or more first predicted fluid properties using one or more pre-trained machine-learning (ML) models. The one or more first predicted fluid properties are predicted based at least partially upon the one or more mud gas properties. The method also includes comparing the one or more measured fluid properties to the one or more first predicted fluid properties. The method also includes re-training the one or more pre-trained ML models to produce one or more re-trained ML models in response to the comparison.

Abstract: Methods (and related apparatus) include obtaining data regarding a measured property. The measured property includes an amount of each of predetermined hydrocarbons in a gas sample extracted from drilling fluid exiting a wellbore having a hydrocarbon resource. An unknown characteristic of an investigated fluid property of the hydrocarbon resource is predicted utilizing the obtained input data and one or more predetermined models each built via statistical classification and regression analysis of a preexisting database containing records. Each record includes known characteristics of fluid properties of a different one of known reservoir fluids. The fluid properties include the investigated fluid property and the measured property. The investigated fluid property includes a fluid type of the hydrocarbon resource, an amount of at least one additional hydrocarbon, gas-oil ratio, or stock tank oil density.

Abstract: Systems and methods presented herein provide for a box chain conveyor adsorption moving bed that separates carbon dioxide from a gas mixture. A box chain conveyor is oriented around a wall, including a chain that moves in a closed loop around the wall. One side of the box chain conveyor is in an adsorption section and an opposite second side is in a desorption section. Particle boxes contain adsorbent particles, and the chain moves the particle boxes around the wall in the closed loop. Heated gas passes through the desorption section, causing CO2 to desorb from particle boxes in the desorption section. Desorbed CO2 is expelled from an output.

Abstract: Systems and methods presented herein provide for a screw conveyor adsorption moving bed that separates carbon dioxide from a gas mixture. Adsorbent particles are transported between an adsorption section of the reactor, which can be an outer column, and a desorption section, which can be an inner column. The particle transport is facilitated by the screw conveyor located inside the inner column. The screw conveyor is specially designed to have a hollow screw, shaped as a spiral surface, attached to a central shaft. The screw surface is also equipped with plurality of holes and a flexible edge attachment to seal against the cylindrical surface. The hollow shape allows the gas to flow from the inlet of the shaft to the particles through the holes on the screw, thus creating uniform gas distribution.

Abstract: Systems and methods presented herein generally relate to a formation testing tool configured to determine whether a formation fluid being tested is a bubble point fluid or a dew point fluid. For example, in certain embodiments, a method includes depressurizing a flowline of a formation testing tool. The flowline contains a formation fluid having a gas-to-oil ratio (GOR) within a predetermined GOR range. The method also includes determining, using a fluid analysis module of the formation testing tool, whether the formation fluid is a bubble point fluid or a dew point fluid by analyzing distribution of bubbles in the formation fluid that are caused by the depressurization of the flowline.

Abstract: Systems and methods estimating the SARA fractions of a reservoir fluid. This method uses a machine learning (ML) based model to predict the SARA fractions of a reservoir fluid. The ML models are trained using conventional laboratory data, such as fluid composition from gas chromatography, SARA measurement, Asphaltene onset pressure (AOP) etc. Reservoir fluid can be pumped from a wellbore into a downhole fluid analyzer tool. The downhole fluid analyzer tool can take measurements indicating the presence and levels of certain particles in the fluid. The measurements can be applied to the ML models to estimate SARA levels in the reservoir fluid.

Abstract: A method for predicting fluid properties includes measuring one or more measured fluid properties of a mud gas at a surface of a wellbore. The method also includes measuring one or more mud gas properties of the mud gas at the surface of the wellbore. The method also includes predicting one or more first predicted fluid properties using one or more pre-trained machine-learning (ML) models. The one or more first predicted fluid properties are predicted based at least partially upon the one or more mud gas properties. The method also includes comparing the one or more measured fluid properties to the one or more first predicted fluid properties. The method also includes re-training the one or more pre-trained ML models to produce one or more re-trained ML models in response to the comparison.

Abstract: A system for capturing a target species from an exhaust gas stream generated by at least one engine at a surface of a wellbore utilized in reservoir stimulation for subsurface energy recovery. The system includes a heat exchanging system for cooling the exhaust gas stream to a predetermined temperature. The system includes a water separation unit for separating a liquid from the cooled exhaust gas stream. The system includes a target species capture module for capturing the target species from the cooled exhaust gas stream. The system includes a target species regeneration module to extract the captured target species. The system includes a target species compression module for liquefying the captured target species. The system includes a target species storage module for storing the liquified target species, wherein the system is mounted on a mobile platform for transportation to and from the surface of the wellbore.

Abstract: Embodiments present a method for fluid type identification from a downhole fluid analysis that uses machine learning techniques that are trained and derived from a computer model using pressure, temperature and downhole optical characteristics of sampled fluid.

Abstract: Embodiments presented provide for a method and design of heat effective rotated packed beds wherein rotating packed bed technologies have heat transfer capabilities to enhance separation, absorbing and desorbing capabilities. Such beds are used in industries including heavy processing, chemical, petrochemical and pharmaceutical industries.

Abstract: Embodiments presented provide for a multirotational counter rotating reactor. The reactor is configured to accept a fluid stream and separate the fluid stream into high quality liquid and gaseous phases through spinning of the sets of discs as well as through performing a heat transfer to the fluid stream.

Abstract: A microfluidic apparatus includes a substrate defining a microchannel having inlet and an outlet defining a length of the microchannel. The microchannel has a main channel extending from the inlet to the outlet, and a plurality of side cavities extending from the main channel. The cavities are in fluid communication with the main channel. A method includes introducing a sample into the microchannel through the inlet to fill the entire microchannel, and then introducing a solvent into the microchannel through the inlet at a controlled flow rate and inlet pressure. A developed solvent front then moves along the main channel from the inlet to the outlet while displacing the sample in the main channel. Images of the microchannel are acquired as the front moves, and a miscibility condition is determined based on the images.

Abstract: Methods and apparatus provide for determining a reservoir fluid phase envelope from downhole fluid analysis data using machine learning techniques.

Abstract: Embodiments present a method for fluid type identification from a downhole fluid analysis that uses machine learning techniques that are trained and derived from a computer model using pressure, temperature and downhole optical characteristics of sampled fluid. The method comprises collecting optical spectral data for a downhole fluid; providing the collected optical spectral data to a trained classification module; processing the collected optical spectral data with the trained classification module configured to determine a fluid type classification; and determining a fluid type based upon the classification based upon the trained classification module.

Abstract: A technique facilitates detection and analysis of constituents, e.g. chemicals, which may be found in formation fluids and/or other types of fluids. The technique comprises intermittently introducing a first fluid and a second fluid into a channel in a manner which forms slugs of the first fluid separated by the second fluid. The intermittent fluids are flowed through the channel to create a mixing action which mixes the fluid in the slugs. The mixing increases the exchange, e.g. transfer, of the chemical constituent between the second fluid and the first fluid. The exchange aids in sensing an amount of the chemical or chemicals for analysis. In many applications, the intermittent introduction, mixing, and measuring can be performed in a subterranean environment.

Abstract: Methods (and related apparatus) include obtaining data regarding a measured property. The measured property includes an amount of each of predetermined hydrocarbons in a gas sample extracted from drilling fluid exiting a wellbore having a hydrocarbon resource. An unknown characteristic of an investigated fluid property of the hydrocarbon resource is predicted utilizing the obtained input data and one or more predetermined models each built via statistical classification and regression analysis of a preexisting database containing records. Each record includes known characteristics of fluid properties of a different one of known reservoir fluids. The fluid properties include the investigated fluid property and the measured property. The investigated fluid property includes a fluid type of the hydrocarbon resource, an amount of at least one additional hydrocarbon, gas-oil ratio, or stock tank oil density.

Abstract: A microfluidic apparatus has a microchannel that includes at least one vertically oriented segment with a top section having a relatively wide opening and a bottom section having a relatively narrow opening. The top section is larger in volume relative to the bottom sections, and the middle sections taper down in at least one dimension from the top section to the bottom section. One or tens or hundreds of vertically-oriented segments may be provided, and they are fluidly coupled to each other. Each segment acts as a pressure-volume-temperature (PVT) cell, and the microchannel apparatus may be used to determine a parameter of a fluid containing hydrocarbons such as the dew point of the fluid or the liquid drop-out as a function of pressure.

Abstract: A microfluidic apparatus includes a substrate defining a microchannel having inlet and an outlet defining a length of the microchannel. The microchannel has a main channel extending from the inlet to the outlet, and a plurality of side cavities extending from the main channel. The cavities are in fluid communication with the main channel. A method includes introducing a sample into the microchannel through the inlet to fill the entire microchannel, and then introducing a solvent into the microchannel through the inlet at a controlled flow rate and inlet pressure. A developed solvent front then moves along the main channel from the inlet to the outlet while displacing the sample in the main channel. Images of the microchannel are acquired as the front moves, and a miscibility condition is determined based on the images.

Abstract: An optical sensor and corresponding method of operation can detect a phase transition and/or related property of a hydrocarbon-based analyte. The optical sensor includes an optical element with a metallic film coupled or integral thereto, with a sample chamber holds the hydrocarbon-based analyte such that the hydrocarbon-based analyte is disposed adjacent the metallic layer. The optical sensor further includes a light source configured to direct light through the optical element such that the light is reflected by the metallic layer under conditions of surface plasmon resonance. The optical sensor analyzes the reflected light to detect a phase transition and/or related property of a hydrocarbon-based analyte.

Abstract: An optical sensor includes a flow cell permitting flow of a hydrocarbon-based analyte therethrough. A metallic film is disposed adjacent or within the flow cell. At least one optical element directs polychromatic light for supply to an interface of the metallic film under conditions of surface plasmon resonance (SPR) and directs polychromatic light reflected at the interface of the metallic film (which is sensitive to SPR at such interface and thus provides an SPR sensing region within the flow cell) for output to at least one spectrometer that measures spectral data of such polychromatic light. A computer processing system is configured to process the measured spectral data over time as the hydrocarbon-based analyte flows through the flow cell to determine SPR peak wavelength over time and to process the SPR peak wavelength over time to determine at least one property related to phase transition of the analyte.