Abstract: A system, method, and computer program product for reservoir reserves estimation that includes at least one processing component, at least one memory component, a well data manager, a classification module, and an estimation module. The well data manager consolidates well data for a subject well and at least one neighbor well. The classification module includes a search component that selects at least one closest neighbor well from the neighbor wells. The classification module also includes a similarity matching component that determines a log signature distance between the at least one closest neighbor well and the subject well, as well as an analog selector that selects one or more analog wells from the at least one closest neighbor well. The estimation module includes a decline estimator that generates group decline rates for the one or more analog wells and a subject decline rate based on the group decline rates.

Abstract: A system, method, and computer program product for reservoir reserves estimation that includes at least one processing component, at least one memory component, a well data manager, a classification module, and an estimation module. The well data manager consolidates well data for a subject well and at least one neighbor well. The classification module includes a search component that selects at least one closest neighbor well from the neighbor wells. The classification module also includes a similarity matching component that determines a log signature distance between the at least one closest neighbor well and the subject well, as well as an analog selector that selects one or more analog wells from the at least one closest neighbor well. The estimation module includes a decline estimator that generates group decline rates for the one or more analog wells and a subject decline rate based on the group decline rates.

Abstract: Described are techniques for predicting gradual performance degradation with non-linear characteristics. The techniques including a method comprising inputting a new data sample to a failure prediction model, wherein the failure prediction model is trained using a labeled historical dataset, wherein respective data points are associated with a look-back window and a prediction horizon to create respective training samples, wherein the respective training samples are clustered in a plurality of clusters, and wherein the plurality of clusters are each associated with a normalcy score and an anomaly score. The method further comprises outputting a classification associated with the new data sample based on comparing a first anomaly score of a first cluster of the plurality of clusters that includes the new data sample to an average anomaly score of clusters of the plurality of clusters having the normalcy score greater than the anomaly score.

Abstract: Described are techniques for predicting gradual performance degradation with non-linear characteristics. The techniques including a method comprising inputting a new data sample to a failure prediction model, wherein the failure prediction model is trained using a labeled historical dataset, wherein respective data points are associated with a look-back window and a prediction horizon to create respective training samples, wherein the respective training samples are clustered in a plurality of clusters, and wherein the plurality of clusters are each associated with a normalcy score and an anomaly score. The method further comprises outputting a classification associated with the new data sample based on comparing a first anomaly score of a first cluster of the plurality of clusters that includes the new data sample to an average anomaly score of clusters of the plurality of clusters having the normalcy score greater than the anomaly score.

Abstract: One aspect includes a method for use with a plurality of steam assisted gravity drainage wells. The method includes designing a first modeling framework which provides a model of total output for the plurality of wells from one or more input variables for respective ones of the plurality of wells. The method also includes designing a second modeling framework which provides a model of output for a given one of the plurality of wells based at least in part on one or more input variables for the given one of the plurality of wells and one or more input variables for at least another one of the plurality of wells. The method further includes utilizing the first and second modeling frameworks to determine an optimal configuration for the wells and configuring the well to operate with the determined optimal configuration.

Abstract: One aspect includes a method for use with a steam assisted gravity drainage well. The method includes generating an analytical framework for the well at least in part by modeling one or more observable variables as a function at least of one or more control variables; and modeling one or more output variables as a function at least of at least one of the one or more control variables; and at least one of the one or more observable variables. The method further includes utilizing the analytical framework to determine an optimal configuration for the well, the optimal configuration including a set of one or more values for the one or more control variables which produce one or more desired values for the one or more output variables; and configuring the well to operate with the determined optimal configuration.

Abstract: One aspect includes a method for use with a steam assisted gravity drainage well. The method includes generating an analytical framework for the well at least in part by modeling one or more observable variables as a function at least of one or more control variables; and modeling one or more output variables as a function at least of at least one of the one or more control variables; and at least one of the one or more observable variables. The method further includes utilizing the analytical framework to determine an optimal configuration for the well, the optimal configuration including a set of one or more values for the one or more control variables which produce one or more desired values for the one or more output variables; and configuring the well to operate with the determined optimal configuration.

Abstract: One aspect includes a method for use with a plurality of steam assisted gravity drainage wells. The method includes designing a first modeling framework which provides a model of total output for the plurality of wells from one or more input variables for respective ones of the plurality of wells. The method also includes designing a second modeling framework which provides a model of output for a given one of the plurality of wells based at least in part on one or more input variables for the given one of the plurality of wells and one or more input variables for at least another one of the plurality of wells. The method further includes utilizing the first and second modeling frameworks to determine an optimal configuration for the wells and configuring the well to operate with the determined optimal configuration.