A method for calibrating forecasts involving temperature, precipitation, and other weather related variables is provided. In an embodiment historical ensemble-based forecasts and historical observations are received by an agricultural intelligence computing system. Historical differences are determined between the forecasts and the observations corresponding to the forecasts and stored in the volatile memory of the agricultural intelligence computing system. The agricultural intelligence computing system receives current ensemble-based forecasts and a request for improved forecasts. The agricultural intelligence computing system retrieves the historical differences and uses a combination of the historical differences and the current ensemble-based forecasts to create probability distributions for the weather for each lead day. The agricultural intelligence computing system then samples from the probability distributions to create improved ensemble-based forecasts at the requested location.

A method, system and computer program product are disclosed for integrating plural modalities of information to obtain values for a specified attribute of a given system. In one embodiment, the method comprises acquiring data of a first modality, conveying a first source of data of a first type of the system; configuring simulator with settings of physical sensors; acquiring data of a second modality from the system, conveying a second source of data of a second type of the system. The method further comprises converting the data of the second modality to data of the first type, while configuring a virtual set of sensors to enable acquisition of the converted data of the second modality; and configuring adjoints equipped simulator with settings of the virtual sensors, to mimic collection of data of the first type, while configured to measure data of second type.

The present invention is a method for determining at least one of the quantity and the quality of the hydrocarbons present in a sedimentary basin, by use of a numerical basin simulator containing a kinetic model. The kinetic model is applied with kinetic parameters in order to reproduce the transformation of the organic matter into at least one chemical compound under the effect of an increase in temperature. The present invention converts kinetic parameters relating to a first compositional representation into kinetic parameters relating to a second compositional representation, by use of a compositional reference established from reference source rocks and from the level of transformation of a reference rock.

A modeling method is provided. The modeling method includes: extracting multiple pieces of logging data corresponding to a plurality of logging characteristic parameters at different drilling depths of a sample well, based on a logging information of the sample well; marking the different drilling depths based on a lost circulation information of the sample well to distinguish lost circulation points and non-lost circulation points; and classifying the lost circulation points and the non-lost circulation points by adopting a random forest algorithm, based on the plurality of logging characteristic parameters and the multiple pieces of marked logging data at the different drilling depths, to establish a plurality of corresponding relations between the logging characteristic parameters and a lost circulation or non-lost circulation result, so as to obtain a diagnosis model.

Methods of exploiting a formation containing a reservoir of hydrocarbons utilize a gas-liquid drift-flux (DF) model for a multi-segmented wellbore (MSW). The DF model is provided for use in conjunction with a reservoir simulator. The DF model is configured to account for pipe inclinations of the MSW between 90 and +90 including horizontal or near-horizontal wellbores in addition to vertical and slanted wellbores. The DF model is based on mixture velocity as opposed to superficial velocities, thereby permitting the DF model to be integrated with reservoir models that utilize mixture velocity. The DF model can also be continuous and differentiable over all primary variables.

A computer-implemented method and a system are provided for optimizing reservoir simulation runtime and storage by hashing reservoir model structural and initialization data. A checksum is calculated for model structural data produced from a reservoir simulation study. A hash table is queried for the checksum. A determination is made whether the checksum exists in the hash table. When a determination is made that the checksum exists in the hash table, soft links are generated to physical locations of reservoir structure files containing the model structural data. When a determination is made that the checksum does not exist in the hash table, the following occurs. New reservoir structure files are generated for the model structural data. A new hash table entry is generated containing record information identifying contents of the new reservoir structure files. The hash table is updated with the new hash table entry.

The invention relates to a method and a computer-implemented invention for numerical modeling of a geological structure. The present invention solves the problem providing a method for use in the numerical simulation of the in-situ stress in a geological structure represented by a domain located under its external ground surface S. The method comprises mainly two steps: determining a first state of in-situ stress in the domain by means of six stress components and a second step determining a correction of the first state of stress in order to satisfy the equilibrium equation.

A geometric method is described for 3D structural restoration of a subsurface model including receiving data representative of a subsurface volume of interest including one or more chronohorizons and the geometry and topology of any faults of relevance; developing a fault framework model of the subsurface volume of interest; selecting a horizon, the deposition of which represents the geologic time to which the structural model should be restored; developing coordinate transformation constrained by a single datum horizon and, optionally, additional geologic constraints; applying the 3D transformation to all geologic features below and, optionally, above the datum surface; and scaling the vertical coordinates to accurately relate vertical and horizontal dimensions. The method may be executed by a computer system.

A method for determining national crop yields during the growing season is provided. In an embodiment, a server computer system receives agricultural data records for a particular year that represent covariate data values related to plants at a specific geo-location at a specific time. The system aggregates the records to create geo-specific time series for a geo-location over a specified time. The system creates aggregated time series from a subset of the geo-specific time series. The system selects a representative feature from the aggregated time series and creates a covariate matrix for each specific geographic area in computer memory. The system determines a specific state crop yield for a specific year using linear regression to calculate the specific state crop yield from the covariate matrix. The system determines a national crop yield for the specific year using the sum of the state crop yields for the specific year nationally adjusted.

A non-transitory computer readable medium includes a set of instructions that in operation cause a processor to determine at least one modelled parameter of a feature of interest in petroleum exploration. The instructions also cause a processor to assign a likelihood value to each modelled parameter of the at least one modelled parameter and to generate an initial chance map for each modelled parameter of the at least one modelled parameter. Further, the instructions cause a processor to assign a weighting factor for each modelled parameter of the at least one modelled parameter, and to combine the initial chance maps using the weighting factor for each modelled parameter of the at least one modelled parameter to generate a first simulation chance map.