A method can include providing a trained neural network; providing a set of production values where the set includes, for example, a cumulative production value for an interval, an average production value for the interval, a first production value for the interval and a last production value for the interval; and predicting at least one production value for a subsequent interval based at least in part on the trained neural network and the provided set of production values. Various other apparatuses, systems, methods, etc., are also disclosed.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: providing a trained neural network; providing a set of production values for production of a resource from a basin wherein the set comprises a cumulative production value for an interval, an average production value for the interval, a first production value for the interval and a last production value for the interval; and predicting at least one production value for a subsequent interval based at least in part on the trained neural network and the provided set of production values. 2. The method of claim 1 wherein the set of production values consists of the cumulative production value for the interval, the average production value for the interval, the first production value for the interval and the last production value for the interval. 3. The method of claim 1 wherein the set of production values comprise production values for a single well. 4. The method of claim 1 comprising generating the trained neural network by providing historic production data for the interval and the subsequent interval and training a neural network using the provided historic production data. 5. The method of claim 1 wherein the interval and the subsequent interval comprise time intervals measured from commencement of production of the resource from a well. 6. The method of claim 1 wherein the trained neural network is configured to predict at least one production value for an interval based on a set of production values for a prior interval. 7. The method of claim 6 wherein the interval and the prior interval are contiguous in time. 8. The method of claim 1 wherein the trained neural network comprises an input node layer, a hidden node layer and an output node layer. 9. The method of claim 8 wherein the trained neural network comprises node connections and weights. 10. The method of claim 1 wherein the resource comprises gas and wherein the basin comprises a shale formation. 11. A system comprising: a processor; memory operatively coupled to the processor; and instructions stored in the memory and executable by the processor to predict production of a resource from a basin using input values and a set of trained neural networks wherein each of the neural networks in the set corresponds to a different production interval for production of the resource from the basin, 12. The system of claim 11 wherein the different production intervals are contiguous in time. 13. The system of claim 11 wherein the input values comprise a cumulative production value, an average production value, a first production value and a last production value. 14. The system of claim 11 wherein the input values comprise measured values for a first interval. 15. The system of claim 14 wherein output values corresponding to a second interval are output from one of the set of trained neural networks for the first interval and wherein the output values are input to one of the set of trained neural networks for a second interval to output values corresponding to a third interval. 16. The system of claim 11 wherein the set of trained neural networks are trained using training data for at least 5 production wells. 17. One or more computer-readable media comprising computer-executable instructions to instruct a computing system to predict production of a resource from a basin using input values and a set of trained neural networks wherein each of the neural networks in the set corresponds to a different production interval for production of the resource from the basin. 18. The one or more computer-readable media of claim 17 wherein each of the trained neural networks in the set of trained neural networks comprises a cumulative production input parameter, an average production input parameter, a first production input parameter and a last production input parameter. 19. The one or more computer-readable media of claim 17 wherein the resource comprises gas and wherein the basin comprises shale. 20. The one or more computer-readable media of claim 17 wherein to predict production comprises prediction of at least a cumulative production value.