An estimated gas leak flow rate can be determined using a teaching set of concentration profiles, a regression model implemented by a machine-learning subsystem, and a subset of attributes measured within an environment. The teaching set of concentration profiles can include gas flow rates associated with relevant attributes. The regression model can be transformed into a gas leak flow regression model via the machine-learning subsystem using the teaching set. The subset of attributes measured within the environment can be applied to the gas leak flow regression model to determine other attributes absent from the subset of attributes and an estimated gas flow rate for the environment. A gas leak attenuation action can be performed in response to the estimated gas flow rate.

Methods, systems, and non-transitory computer readable media for estimating well interference on a target well from other potential wells in a subsurface volume of interest are disclosed. Exemplary implementations may include: obtaining well implementation data for the target well and the other potential wells; obtaining estimated reservoir volumes as a function of position; generating well overlap between the target well and the other potential wells; generating extraction interference probabilities; generating a representation of a well layout as a function of position in the subsurface volume of interest; and displaying the representation.

The invention relates to the technical field of oilfield exploration, and discloses a 4D quantitative and intelligent diagnosis method and system for spatio-temporal evolution of oil-gas reservoir damage types and extent. The method includes: determining a characteristic parameter characterizing reservoir damage by each of a plurality of factors based on a spatio-temporal evolution simulation equation of reservoir damage by each of the plurality of factors; and determining an effective characteristic parameter characterizing the damage extent of the reservoir based on the characteristic parameter characterizing reservoir damage rby each of the plurality of factors. The invention can quantitatively simulate the characteristic parameters of reservoir damage caused by the various factors and a total characteristic parameter of the reservoir damage. Therefore for a well without reservoir damage, performing quantitative prediction of reservoir damage and spatio-temporal deduction of damage laws is of scientific guidance significance for preventing reservoir damage, and formulating development plans for oil pools and subsequent well stimulation measures, and for a well with reservoir damage, also performing quantitative diagnosis of reservoir damage and spatio-temporal deduction of damage laws achieves optimal design of a declogging measure and improvement or restoration of oil-gas well production and water well injection capacity.

A computer-implemented numerical simulation method for studying a physical system governed by at least one differential equation such as a fluid in motion. The simulation is launched, making it possible to define a simulation domain. In the computation step, a machine learning algorithm is implemented to predict a global solution to the equation in the simulation domain. The computation step includes n consecutive sequences, each sequence includes cutting a piece in the simulation domain followed by predicting a local solution in the piece on the basis of local boundary conditions, n being an integer strictly greater than 1. The prediction step being carried out by a machine learning model, as input, global boundary conditions on the simulation domain.

A smoothed-particle hydrodynamics (SPH)-based fluid analysis simulation apparatus comprises: an input unit for receiving, as an input, data about a plurality of particles, for a fluid analysis simulation; a space formation unit that divides, into a plurality of cells, the space in which the plurality of particles are present, and generates cell indexes on the basis of the locations of the cells in the space where the plurality of particles are present; a particle search unit for searching for at least one neighboring particle that neighbors a target particle, on the basis of particle reference information about the plurality of particles and cell reference information about the plurality of cells; and a flow data calculation unit that calculates flow data between the target particle and the at least one neighboring particle, and performs a fluid simulation on the basis of the flow data for the plurality of particles.

Methods and systems are provided for characterizing a subterranean formation that involve the generation of four 3D geological model of the formation that are updated before and after an enhanced hydrocarbon production process.

A method for stimulation of a well in a material formation which includes a workflow for the design of hole-size distribution in the liner of a LEL liner system is modelled, wherein a solution strategy for providing an initial estimate of the number of holes per segment honours the acid coverage per segment and the drop in pressure (dp) across the last one of the holes, where the initial estimate can be found from the relationship between interstitial velocity, pump rate, and total cross-sectional hole area for a particular discharge coefficient and liner configuration.

A computer-implemented method for constrained multi-phase virtual flow metering and forecasting is described. The method includes predicting instantaneous flow rates and forecasting future target flow rates and well dynamics. The method includes constructing a virtual sensing model trained using forecasted target flow rates and well dynamics. The method includes building a constrained forecasting model by combining unconstrained flow forecasting models, well dynamics models, and virtual sensing models, wherein the constrained forecasting model forecasts multi-phase flow rates.

A method includes establishing a database including one or more characteristics of one or more reactants and a historical data subset; determining, utilizing a machine learning algorithm trained with data stored in the database, a combination of the reactants and a reaction condition to be used for synthesis of a nanofluid; and synthesizing the nanofluid based on the combination of reactants and the reaction condition.

A smoothed-particle hydrodynamics (SPH)-based fluid analysis simulation apparatus comprises: an input unit for receiving, as an input, data about a plurality of particles, for a fluid analysis simulation; a space formation unit that divides, into a plurality of cells, the space in which the plurality of particles are present, and generates cell indexes on the basis of the locations of the cells in the space where the plurality of particles are present; a particle search unit for searching for at least one neighboring particle that neighbors a target particle, on the basis of particle reference information about the plurality of particles and cell reference information about the plurality of cells; and a flow data calculation unit that calculates flow data between the target particle and the at least one neighboring particle, and performs a fluid simulation on the basis of the flow data for the plurality of particles.