Flow network model analysis

Abstract

In one implementation, a method includes generating a manifold predictive model configured to calculate an initial virtual measurement associated with an oil field comprising a plurality of oil wells. The manifold predictive model can be based on one or more predictive models associated with one or more components of the oil field. The method also includes receiving data characterizing one or more pressure measurements and flow measurements obtained in the oil field. The method further includes determining a prospective sensor location of a first prospective sensor in the oil field. The first prospective sensor can be configured to detect an oil field parameter. The manifold predictive model can be configured to receive data characterizing the detected oil field parameter and generate an updated virtual measurement. The method also includes providing the prospective sensor location and the identity of the first prospective sensor.

What is claimed is: 
     
         1 . A method comprising:
 generating a manifold predictive model configured to calculate an initial virtual measurement associated with an oil field comprising a plurality of oil wells, the manifold predictive model based on one or more predictive models associated with one or more components of the oil field;   receiving data characterizing one or more pressure measurements and flow measurements obtained in the oil field,   determining a prospective sensor location of a first prospective sensor in the oil field, the first prospective sensor configured to detect an oil field parameter; and   providing the prospective sensor location and/or the identity of the first prospective sensor.   
     
     
         2 . The method of  claim 1 , wherein the manifold predictive model is associated with a first manifold in the oil field, the first manifold coupled to a plurality of oil wells in the oil field, and wherein the one or more predictive models includes one or more of flow models associated with pipes connecting the first manifold to the plurality of oil wells, and physical equations and/or sensor measurements associated with one or more of the plurality of oil wells. 
     
     
         3 . The method of  claim 2 , wherein the manifold predictive model is configured to calculate a probabilistic estimation indicative of an operating range of a flow rate associated with one or more of oil, gas and water from the first manifold. 
     
     
         4 . The method of  claim 3 , wherein the calculation of probabilistic estimation of flow rates is based on one or more sensor measurements at the first manifold. 
     
     
         5 . The method of  claim 1 , wherein the manifold predictive model is configured to receive data characterizing the detected oil field parameter and generate an updated virtual measurement. 
     
     
         6 . The method of  claim 5 , wherein a first sensitivity associated with the updated virtual measurement is smaller than a second sensitivity associated with the initial virtual measurement. 
     
     
         7 . The method of  claim 1 , wherein at least one of the one or more pressure measurements and flow measurements are obtained at a manifold of the oil field. 
     
     
         8 . A system comprising:
 at least one data processor;   memory coupled to the at least one data processor, the memory storing instructions to cause the at least one data processor to perform operations comprising:
 generating a manifold predictive model configured to calculate an initial virtual measurement associated with an oil field comprising a plurality of oil wells, the manifold predictive model based on one or more predictive models associated with one or more components of the oil field; 
   receiving data characterizing one or more pressure measurements and flow measurements obtained in the oil field,   determining a prospective sensor location of a first prospective sensor in the oil field, the first prospective sensor configured to detect an oil field parameter; and   providing the prospective sensor location and/or the identity of the first prospective sensor.   
     
     
         9 . The system of  claim 8 , wherein the manifold predictive model is associated with a first manifold in the oil field, the first manifold coupled to a plurality of oil wells in the oil field, and wherein the one or more predictive models includes one or more of flow models associated with pipes connecting the first manifold to the plurality of oil wells, and physical equations and/or sensor measurements associated with one or more of the plurality of oil wells. 
     
     
         10 . The system of  claim 9 , wherein the manifold predictive model is configured to calculate a probabilistic estimation indicative of an operating range of a flow rate associated with one or more of oil, gas and water from the first manifold. 
     
     
         11 . The system of  claim 10 , wherein the calculation of probabilistic estimation of flow rates is based on one or more sensor measurements at the first manifold. 
     
     
         12 . The system of  claim 8 , wherein the manifold predictive model is configured to receive data characterizing the detected oil field parameter and generate an updated virtual measurement. 
     
     
         13 . The system of  claim 12 , wherein a first sensitivity associated with the updated virtual measurement is smaller than a second sensitivity associated with the initial virtual measurement. 
     
     
         14 . The system of  claim 12 , wherein at least one of the one or more pressure measurements and flow measurements are obtained at a manifold of the oil field. 
     
     
         15 . A computer program product comprising a machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:
 generating a manifold predictive model configured to calculate an initial virtual measurement associated with an oil field comprising a plurality of oil wells, the manifold predictive model based on one or more predictive models associated with one or more components of the oil field;   receiving data characterizing one or more pressure measurements and flow measurements obtained in the oil field,   determining a prospective sensor location of a first prospective sensor in the oil field, the first prospective sensor configured to detect an oil field parameter;   providing the prospective sensor location and/or the identity of the first prospective sensor.   
     
     
         16 . The computer program product of  claim 15 , wherein the manifold predictive model is associated with a first manifold in the oil field, the first manifold coupled to a plurality of oil wells in the oil field, and wherein the one or more predictive models includes one or more of flow models associated with pipes connecting the first manifold to the plurality of oil wells, and physical equations and/or sensor measurements associated with one or more of the plurality of oil wells. 
     
     
         17 . The computer program product of  claim 16 , wherein the manifold predictive model is configured to calculate a probabilistic estimation indicative of an operating range of a flow rate associated with one or more of oil, gas and water from the first manifold. 
     
     
         18 . The computer program product of  claim 17 , wherein the calculation of probabilistic estimation of flow rates is based on one or more sensor measurements at the first manifold. 
     
     
         19 . The computer program product of  claim 15 , wherein the manifold predictive model is configured to receive data characterizing the detected oil field parameter and generate an updated virtual measurement. 
     
     
         20 . The computer program product of  claim 19 , wherein a first sensitivity associated with the updated virtual measurement is smaller than a second sensitivity associated with the initial virtual measurement.