Methods and systems for supply of fuel for a turbine-driven fracturing pump system used in hydraulic fracturing may be configured to identify when the supply pressure of primary fuel to a plurality of gas turbine engines of a plurality of hydraulic fracturing units falls below a set point, identify a gas turbine engine of the fleet of hydraulic fracturing units operating on primary fuel with highest amount of secondary fuel available, and to selectively transfer the gas turbine engine operating on primary fuel with the highest amount of secondary fuel from primary fuel operation to secondary fuel operation. Some methods and systems may be configured to transfer all gas turbine engines to secondary fuel operation and individually and/or sequentially restore operation to primary fuel operation and/or to manage primary fuel operation and/or secondary fuel operation for portions of the plurality of gas turbine engines.

A method includes supplying a plurality of generators, each generator in electrical communication with a switchgear with each switchgear in data communication with a generator data management system. The method also includes supplying a plurality of electrically driven fracturing pumps with each electrically driven fracturing pump in data communication with pump data management system. Further, the method includes supplying a load shedding system, the load shedding system in data communication with the generator data management system and a pump control system, the pump control system in data communication with the pump data management system. The method includes determining which pumps should have speed reduced by the load shedding system and reducing the speed of the pumps determined by the load shedding system using the pump control system.

A method includes supplying a plurality of generators, each generator in electrical communication with a switchgear with each switchgear in data communication with a generator data management system. The method also includes supplying a plurality of electrically driven fracturing pumps with each electrically driven fracturing pump in data communication with pump data management system. Further, the method includes supplying a load shedding system, the load shedding system in data communication with the generator data management system and a pump control system, the pump control system in data communication with the pump data management system. The method includes determining which pumps should have speed reduced by the load shedding system and reducing the speed of the pumps determined by the load shedding system using the pump control system.

A system and method of simulating fluid flow in a hydrocarbon reservoir is disclosed. The method includes obtaining a coarse grid model of the hydrocarbon reservoir and a trajectory of a wellbore that penetrates the hydrocarbon reservoir, and determining an initial grid geometry surrounding the trajectory. The method further includes constructing a reservoir simulation grid, conformal to the initial grid geometry in a first region in a vicinity of the wellbore and conformal with the coarse grid model in a second region more distant from the wellbore than the first region, and performing a hydrocarbon reservoir simulation, modeling a flow of fluid in the hydrocarbon reservoir based, at least in part, on the reservoir simulation grid.

A method for recording data relating to the performance of an oil and gas flow network uses statistical data to represent raw data in a compact form. Categories are assigned to time intervals in the data. The method comprises: (1) gathering data covering a period of time, wherein the data relates to the status of one or more control point(s) within the flow network and to one or more flow parameter(s) of interest in one or more flow path(s) of the flow network; (2) identifying multiple time intervals in the data during which the control points and the flow parameter(s) can be designated as being in a category selected from multiple categories; (3) assigning a selected category of the multiple categories to each one of the multiple datasets that are framed by the multiple time intervals; and (4) extracting statistical data representative of some or all of the datasets identified in step (2) to thereby represent the original data from step (1) in a compact form including details of the category assigned to each time interval in step (3).

A hydrocarbon production field layout comprising a first pipeline (1) with a first inner diameter and a second pipeline (2) with the first inner diameter. A cut off valve (20) with an inner bore with the first diameter, is arranged in a connecting arrangement between an end of the first pipeline (1) and an end of the second pipeline (2). At least one dual main header manifold (3) is in fluid connection with at least one hydrocarbon well (8, 9). A first branch pipe (16, 18) with a first valve (5, 6) is branched off from the first pipeline (1) and a second branch pipe (17, 19) with a second valve (5, 7) is branched off from the second pipeline (2). The branch pipes are connected to the at least one manifold (3, 4).

A method and apparatus for forecasting oil production from an oil well in a geological formation includes receiving a plurality of sets of predicted geological data, for each of the plurality of sets of predicted geological data, determining a probability for the predicted geological data of the formation, iteratively selecting one of the plurality of sets of predicted geological data using Monte Carlo sampling based on the determined probabilities, assigning the selected set of predicted geological data to a cluster of historical data, and for each set of historical data of the cluster generating a predicted oil production rate as a function of time utilizing a machine learning based oil model, generating, based on the predicted oil production rates, a forecasted oil production rate, determining, based on the forecasted oil production rate, a preferred operating parameter for the well, and operating based on the preferred operating parameter.

A method of forecasting well production in an accurate and computational cost-efficient manner implementing a hybrid, iterative approach which is computationally efficient, numerically stable, and improves the accuracy of results. The iterative method of forecasting well production can estimate a set of scaling factor, determining the average adjusted pressure in the matrix, conductive reservoir volume, and oriented hydraulic fracture, applying an algorithm to convert the average adjusted pressure to an actual average pressure, using actual average reservoir pressure to estimate a new set of scaling factor, estimating a relative error based upon the new scaling factor, determining if the relative error is within a user-defined tolerance, and performing the above steps again if relative error is not within the user-defined tolerance or storing the new scaling factors. The new scaling factors can be used to determine a production rate. A second approach implements statistical, data analytics, and pattern recognition techniques.

A hydrocarbon reservoir is treated with heat to induce gasification, water-gas shift, and/or aquathermolysis reactions to generate gases including hydrogen. The hydrogen alone is produced to the surface by using hydrogen-only membranes in the production wells.

Injecting CO2 that is diluted within water, into a coal seam, which allows for the sequestering and control of downhole CO2 within connected fractures without damaging the subterranean formation.