A system and method for controlling a gas supply to provide gas lift for a production wellbore makes use of Bayesian optimization. A computing device controls a gas supply to inject gas into one or more wellbores. The computing device receives reservoir data associated with a subterranean reservoir to be penetrated by the wellbores and can simulate production using the reservoir data and using a physics-based or machine learning or hybrid physics-based machine learning model for the subterranean reservoir. The production simulation can provide production data. A Bayesian optimization of an objective function of the production data subject to any gas injection constraints can be performed to produce gas lift parameters. The gas lift parameters can be applied to the gas supply to control the injection of gas into the wellbore or wellbores.

Various embodiments described herein provide methods of hydrocarbon management and associated systems and/or computer readable media including executable instructions. Such methods (and by extension their associated systems and/or computer readable media for implementing such methods) may include obtaining geophysical data (e.g., seismic or other geophysical data) from a prospective subsurface formation (that is, a potential formation or other subsurface region of interest for any of various reasons, but in particular due to potential for production of hydrocarbons) and using a trained machine learning (ML) system for direct hydrocarbon indicators (DHI) analysis of the obtained geophysical data. Hydrocarbon management decisions may be guided by the DHI analysis.

Systems and methods for evaluating hydrocarbon properties. At least one of the systems includes: a drilling machine configured to drill a borehole; a plurality of infrared cameras configured to capture infrared image data representing a plurality of infrared images of at least one core sample extracted from the borehole; a computer-readable memory comprising computer-executable instructions; and at least one processor configured to execute the computer-executable instructions, in which when the at least one processor is executing the computer-executable instructions, the at least one processor is configured to carry out operations including: receiving the infrared image data captured by the plurality of infrared cameras; determining, based on the infrared image data, at least one hydrocarbon weight value of the at least one core sample.

Systems and methods of placing wells in a hydrocarbon field based on seismic attributes and quality indicators associated with a subterranean formation of the hydrocarbon field can include receiving seismic attributes representing the subterranean formation and seismic data quality indicators. A cutoff is generated for each seismic attribute and seismic data quality indicator. A weight is assigned to each seismic attribute and seismic data quality indicator. The weighted seismic attributes and data quality indicators are aggregated for each location in the hydrocarbon field. A risk ranking is assigned based on the weighted seismic attributes and data quality indicators associated with each location in the hydrocarbon field based on the cutoffs. A map is generated with each location on the surface of the subterranean formation color-coded based on its assigned risk ranking.

The embodiments of the invention provide an intelligent prediction method and apparatus for reservoir sensitivity, belonging to the technical field of reservoir sensitivity prediction. The method includes: acquiring a reservoir sensitivity influence factor item related to a reservoir sensitivity result to be predicted and numerical values of corresponding reservoir sensitivity influence factors; determining a corresponding type of database according to the reservoir sensitivity influence factor item; determining whether numerical values of reservoir sensitivity influence factors corresponding to core parameters in the numerical values of the reservoir sensitivity influence factors include a first upper boundary value or a first lower boundary value; and using, according to whether the first upper boundary value or the first lower boundary value is included, different intelligent sensitivity prediction models to calculate the reservoir sensitivity result to be predicted.

A method includes activating a first electromagnetic source at a first frequency, acquiring a first set of electromagnetic measurements from a first fiber optic electromagnetic sensor in a first well, wherein the first fiber optic electromagnetic sensor is in electromagnetic communication with the first electromagnetic source. The method also includes acquiring a second set of electromagnetic measurements from a second fiber optic sensor in a second well, wherein the second fiber optic sensor is in electromagnetic communication with the first electromagnetic source. The method also includes determining a formation property based on the first set of electromagnetic measurements and the second set of electromagnetic measurements.

Systems, methods, and computer-readable media for determining the production rate of oil produced from each of a plurality of oil-bearing geological layers in an oil field. In some embodiments, the method comprises allocating injected fluid into each layer of a plurality of oil-bearing geological layers to a plurality of paths from injection sites of injection wells to production wells in each layer by balancing the mass of fluid injected into and the total fluid recovered from each oil-bearing geological layer. In some embodiments, the method comprises calculating estimated geological properties for each path in the plurality of paths to match total oil and injection fluid recovered at each production well in the plurality of production wells. In some embodiments, the method comprises using the estimated geological properties, calculating an oil production rate for each path between an injector well and a production well in a geological layer.

A method and system for estimating clean fluid composition and properties. A method may comprise disposing a downhole fluid sampling tool into a wellbore, wherein the downhole fluid sampling tool comprises optical instrumentation, obtaining a fluid sample with the downhole fluid sampling tool, wherein the fluid sample comprises a reservoir fluid contaminated with a well fluid, identifying input parameters from at least one sensor response on the optical instrumentation, and predicting a clean fluid sample of the reservoir fluid using an asymptote of a dimensional reduction analysis and equation of state. A system may comprise a downhole fluid sampling tool and a processing unit. The downhole fluid sampling tool may further comprise an optical instrumentation operable to obtain fluid samples of a reservoir fluid contaminated with a well fluid while the downhole fluid sampling tool is disposed in a wellbore.

A method and system for determination of hydrocarbon accumulations in a subsurface geological area are disclosed. The method comprises creating a structural framework of the subsurface geological area, calculation of a mechanical stress, identifying trapping mechanisms, predicting of a relative fold movement, and estimating of the formation of the hydrocarbon accumulations, and determining the location of the hydrocarbon accumulations in the subsurface geological area. The system used for the determination of the hydrocarbon accumulations comprises an input device for inputting a plurality of data, a properties module for creating a structural framework using the inputted plurality of the data, a processor for the calculation of compressional and tensional forces, fault patterns, and a relative fold movement, an estimation module for estimating the formation of hydrocarbon accumulations, a locator module for determining the presence of hydrocarbon accumulations, and a memory comprising at least one of the structural framework and a data.

Systems and methods for managing flowback fluids produced during a flowback process in a well are provided. The system includes a well formed in a target zone in a hydrocarbon reservoir, where the well also extends to a disposal zone. The system also includes a check valve or zonal isolation systems. The method includes selecting a disposal zone, directing the formation of a well extending through a target zone and a disposal zone, transporting the flowback fluid from the target zone to the disposal zone during the flowback process, and selectively plugging the well near the disposal zone to prevent migration of the flowback fluid.