Abstract: Alkylated aromatic compounds are present in all hydrocarbon samples. This technology uses aromatic selective size exclusion chromatography (ASSEC) to separate the alkylated aromatic compounds from the hydrocarbon samples. The hydrocarbon samples are obtained from various geographical locations in an oil basin. The distribution of the alkylated aromatic compounds is used to determine hydrocarbon migration indicators. A change in the distribution of the alkylated aromatic compounds between the hydrocarbon samples causes a change in the hydrocarbon migration indicators. The change in the hydrocarbon migration indicators between the hydrocarbon samples is used to determine the direction or pathway of hydrocarbon migration.

Abstract: A computer implemented method that enables feature based estimation of water washing parameters is described. The method includes obtaining light hydrocarbon components from historical data and deriving engineered features from the historical data. The method includes extracting a subset of features from the light hydrocarbon components and engineered features, and training a machine learning model to predict a respective water washing parameter using the extracted subset of features.

Abstract: A computer-implemented method for estimating water washing parameters is described. The method includes estimating, using at least one hardware processor, a gas oil ratio (GOR) by deriving statistical relationships between gas composition ratios. The method includes calculating, using the at least one hardware processor, a C7 transformation ratio (Tr1) and present-day reservoir temperature (PDRT) based on the GOR. The method also includes creating, using the at least one hardware processor, a water washing intensity index based on the GOR, Tr1, and PDRT. Additionally, the method includes integrating, using the at least one hardware processor, the water washing intensity index with a gross depositional environment map, wherein a resulting integrated map is used to guide water washing of accumulations.

Abstract: A computer-implemented method for predicting water washing parameters is described. The method includes building, using at least one hardware processor, a training dataset comprising gas composition data and corresponding water washing parameters. The method includes training, using the at least one hardware processor, a machine learning model using the training dataset to output water washing parameters. Additionally, the method includes predicting, using the at least one hardware processor, water washing parameters of an unseen well in real time, wherein inputs to the trained machine learning model are gas composition data associated with the unseen well and the trained machine learning model outputs the water washing parameters.

Abstract: Systems and methods are disclosed. The method includes obtaining geochemical data and geological data for a number of oil samples and training a machine learning network using the geochemical data and the geological data. Each oil sample includes hydrocarbon molecules and the geochemical data includes abundances of the hydrocarbon molecules. The method further includes obtaining a new oil sample from a subterranean region of interest and determining new geochemical data for the new oil sample using gas chromatography. The method still further includes predicting new geological data for the new oil sample by inputting the new geochemical data into the trained machine learning network.

Abstract: A system for identifying migration direction of natural gases is provided and may include a network of 4He gas sensors and a migration monitoring hub. The network of 4He gas sensors may be operable to identify a 4He concentration in gas samples. The migration monitoring hub may be in communication with the network of 4He gas sensors and may comprise a user interface and a processor. The processor may be operable to determine a direction of increasing 4He concentration and map increasing 4He concentration. The user interface may be operable to display migration information. A method for identifying migration direction of natural gases is also provided and may include isolating a target portion of a petroleum exploration environment, detecting gas samples from a network of 4He gas sensors, identifying a 4He concentration in the gas samples, and determining a direction of increasing 4He concentration in the gas samples.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: A system for identifying migration direction of natural gases is provided and may include a network of 4He gas sensors and a migration monitoring hub. The network of 4He gas sensors may be operable to identify a 4He concentration in gas samples. The migration monitoring hub may be in communication with the network of 4He gas sensors and may comprise a user interface and a processor. The processor may be operable to determine a direction of increasing 4He concentration and map increasing 4He concentration. The user interface may be operable to display migration information. A method for identifying migration direction of natural gases is also provided and may include isolating a target portion of a petroleum exploration environment, detecting gas samples from a network of 4He gas sensors, identifying a 4He concentration in the gas samples, and determining a direction of increasing 4He concentration in the gas samples.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Embodiments provide a method for evaluating a hydrocarbon-bearing formation. The method includes the step of identifying a hydrocarbon sweet spot. The identifying step includes determining a carbon dioxide content of a gas sample retrieved from the hydrocarbon-bearing formation. The identifying step includes determining an isotopic signature of carbon dioxide of the gas sample. The carbon dioxide content of the gas sample retrieved from the hydrocarbon sweet spot can have a mole percentage ranging from 9 percent to 20 percent. The isotopic signature of carbon dioxide of the gas sample retrieved from the hydrocarbon sweet spot can have a ?13C value greater than ?10 per mil. The identifying step can further include determining a cutoff range of the carbon dioxide content corresponding to the hydrocarbon sweet spot. The cutoff range can have a mole percentage ranging from 9 percent to 20 percent. The identifying step can further include obtaining a gas flow rate of the hydrocarbon-bearing formation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Embodiments provide a method for evaluating a hydrocarbon-bearing formation. The method includes the step of identifying a hydrocarbon sweet spot. The identifying step includes determining a carbon dioxide content of a gas sample retrieved from the hydrocarbon-bearing formation. The identifying step includes determining an isotopic signature of carbon dioxide of the gas sample. The carbon dioxide content of the gas sample retrieved from the hydrocarbon sweet spot can have a mole percentage ranging from 9 percent to 20 percent. The isotopic signature of carbon dioxide of the gas sample retrieved from the hydrocarbon sweet spot can have a ?13C value greater than ?10 per mil. The identifying step can further include determining a cutoff range of the carbon dioxide content corresponding to the hydrocarbon sweet spot. The cutoff range can have a mole percentage ranging from 9 percent to 20 percent. The identifying step can further include obtaining a gas flow rate of the hydrocarbon-bearing formation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting seepage of hydrocarbons in subterranean zones. In one aspect, a method includes detecting hydrocarbon seepage at multiple different sampling depths from a surface in a surveyed geographic region, comparing each of the hydrocarbon seepage at the multiple different sampling depths, wherein hydrocarbon seepage at a reference depth is known, and determining hydrocarbon seepage through the surveyed geographic region based on a result of the comparison.