Integrated resource monitoring system with interactive logic control for well water extraction

• US 8,892,221 B2
• Filed: 11/23/2010
• Issued: 11/18/2014
• Est. Priority Date: 09/18/2007
• Status: Active Grant

• Current Assignee: Groundswell Technologies
• Original Assignee: Groundswell Technologies, Inc.
• Inventors: Kram, Mark, Loaiciga, Hugo
• Primary Examiner(s): VON BUHR, MARIA N
• Application Number:
  US12/952,504
• Publication Number:
  US 20110106317A1
• Time in Patent Office: 1,456 Days
• Field of Search: 700 28- 31, 700 47- 51, 700/95, 700/97, 700 99-102, 700/117, 706 14- 19, 34087001-87007, 340/870.09, 340/870.11, 340/500, 340/540, 340603-606, 340/612, 340/616, 340/618, 210/170.01, 210/170.07, 703/10
• US Class Current: 700/51
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/06 Energy or water supply

Abstract

A system for resource usage optimization employs an automatically controlled sensor suite providing data to a computer system for the analysis of spatial relationships of the sensors and resources. A control module incorporates an interactive logic, in an exemplary embodiment of well-stream coupled dynamic or game theory engines, operating in conjunction with the spatial data processing algorithms, GIS in an exemplary embodiment, receives as an input an objective function set for the use of the resource and constraint sets which are then monitored by the sensor suite. Incoming data is compared to the constraint sets and upon impact to any of the elements of the objective function set, creates a report/alarm for action or to trigger a corrective action.

Claims

1. A real-time automated system for resource usage optimization for water well water monitoring comprising:

a plurality of automatically controlled sensor suites monitoring flow rates and levels of multiple extraction wells and aquifer replenishment sources including at least one monitoring well proximate the extraction wells;

a computer system having

GIS data processing algorithms;

a control module incorporating an interactive logic, operating in conjunction with the GIS data processing algorithms and receiving as an input an objective function set, said control module further incorporating resource and constraint sets, the objective function set operable in the interactive logic allowing maximizing of water withdrawal capability in a most economically efficient manner by multiple users while avoiding salt water intrusion into a well from overdraw conditions and the constraint sets include response of the aquifer modeled from static data including historical permeability and storage capacity, flow rates and water table level history;

said control module receiving data monitored by the sensor suites;

said control module comparing the received data to the constraint sets;

a report/alarm for action responsive to the control module upon impact to the objective function set; and

,

a constraints set calculator responsive to the comparison by the control module for providing the sensor suite input data for update of the constraint sets.

2. The real-time automated system for resource usage optimization for water well water monitoring as defined in claim 1 wherein game theory is employed as the interactive logic to establish optimum flow rates within limitations of the constraint sets.

3. The real-time automated system for resource usage optimization for water well water monitoring as defined in claim 2 wherein flow rate monitoring accomplished at a selected one of the multiple extraction wells is employed to validate/update the constraint sets for the Game Theory for closed loop operation.

4. The real-time automated system for resource usage optimization for water well water monitoring as defined in claim 1 further wherein the control module provides automatic adjustment of pumping rates based on model output where an impact to an element of the objective function set is exceeding a predetermined threshold.

5. A real-time system automated for resource usage optimization for assuring a river water level minimum associated with multiple extraction wells drawn upon for use by multiple users comprising:

a plurality of automatically controlled sensor suites monitoring flow rates and levels of multiple extraction wells proximate a river and river water level;

a computer system having

spatial data processing algorithms;

a control module incorporating an interactive logic, operating in conjunction with the spatial data processing algorithms and receiving as an input an objective function set for the use by resource and constraint sets, the objective functions operating in the interactive logic allowing maximizing water withdrawal capability in the most economically efficient manner by multiple users while avoiding reduction of river water level below a predetermined minimum from overdraw conditions and the constraint sets include response of the river level modeled from static data including historical permeability and storage capacity, flow rates and water table level history;

said control module receiving data monitored by the sensor suites;

said control module comparing the received data to the constraint sets;

a report/alarm responsive to said control module for action upon exceeding a threshold of any element of the objective function set;

said control module providing automatic adjustment of pumping rates based on a model output and whether thresholds have been exceeded; and

,

a constraints set calculator responsive to the comparing of received data to the constraint sets by the control module and providing the sensor suite input data for update of the constraint sets for remodeling of interactive logic calculations.

6. The real-time automated system for resource usage optimization for assuring river level as defined in claim 5 wherein a radial flow equation with constant head boundary condition is employed as the interactive logic to establish the optimum flow rates for the desired economic maximization.

7. The real-time automated system for resource usage optimization for assuring river level as defined in claim 6 wherein flow rate monitoring accomplished at the withdrawal well and level monitoring of the river is employed to validate/update the constraints sets for the radial flow equation wherein the constant head boundary condition is solved for closed loop operation.

8. A method for real-time automated resource usage optimization comprising:

providing a plurality of automatically controlled sensor suites at active wells and monitoring wells;

providing a computer system having spatial data processing algorithms and a control module incorporating an interactive logic,

operating the control module in conjunction with the spatial data processing algorithms;

receiving as an input an objective function set for use of constraint sets, said constraint sets including a saltwater intrusion constraint associated with direction of flow near a salt-fresh water interface and an associated water level;

receiving data monitored by the sensor suites;

comparing the received data to the constraint sets;

presenting data for user review in a graphical user interface (GUI);

creating a report/alarm for action upon exceeding a threshold of any element of the objective function set; and

,

recalculating the constraints set responsive to the comparison of received data and constraint sets using the sensor suite input data for update of the constraint sets for remodeling of interactive logic calculations.

9. The method of claim 8 wherein the step of recalculating comprises:

generating initial predictions and modeling based on the constraint sets, and data monitored by the sensor suites;

storing the initial predictions and modeling in the system with received data monitored by the sensor suites;

generating both measured and estimated water level distributions for specific time steps of interest;

interpolating the measured and estimated water level distributions over an entire water basin or stream well interaction system using the spatial data processing algorithms;

comparing measured and estimated water level distributions and comparing flow rates and/or stream levels to the initial predictions;

determining if measured and estimated water level distructions are in agreement within an acceptable error tolerance;

if so, continuing receiving data monitored by the sensor suites;

if not, substituting actual received data monitored by the sensor suites into Theis or Neuman model calculations for a selected time set for reverse calculation of one or more of constraints in the constraint sets as revised constraints;

validating the revised constraints by comparison of newly calculated estimates with the revised constraints as compared to a selected time set of prior actual received data monitored by the sensor suites;

iterating as needed to establish a match within acceptable tolerance of the calculated estimates and actual received data monitored by the sensor suites;

imposing the new constraints set for future predictions.

10. The method of claim 9 wherein transmissivity (T) and storativity (S) are constraints in the constraint sets and the step of substituting actual data results in reverse calculation of T and S.

11. The method of claim 8 wherein pumping rates, water level and stream flow rates, and water level distributions are measured by the sensors in the system at active wells, at measurement wells.

12. The method of claim 10 wherein the step of substituting actual received data monitored by the sensor suites comprises:

minimizing the sum of square deviations between measured values of withdrawn flow wherein the objective function set involves T and S;

said minimizing of the sum of squared deviations accomplished by nonlinear optimization in which, starting with values of T and S used in the aprevious period in which withdrawn flow was estimated, T and S are changed using a two-dimensional Newton-Raphson search method until convergence to optimal values of T and S is achieved.

13. The method of claim 12 wherein an emphasis on T or S is selected for creating convergence of the search method with GUI controls.

14. The method of claim 8 further comprising:

determining a time period for data selection for the step of presenting; and

,

presenting interpolated measurements/estimates in that time period in a user selectable format.

15. The method of claim 14 wherein the step of determining a time period constitutes adjusting a slider in the GUI controls.

16. The method of claim 14 wherein the user selectable format is a histogram of selected wells.

17. The method of claim 16 wherein graphical display of well location is provided.

18. The method of claim 8 wherein the interactive logic comprises game theory and the step of updating the constraint set assumptions comprises the steps of:

maximizing QT G Q+QT z+c with respect to Q subject to;

B Q<

=b;

defining flow rate for each well.

19. A real-time system automated for resource usage optimization for assuring a river water level minimum associated with multiple extraction wells drawn upon for use by multiple users comprising:

a plurality of automatically controlled sensor suites monitoring flow rates and levels of multiple extraction wells proximate a river and river water level;

a computer system having

spatial data processing algorithms;

a control module incorporating an interactive logic, operating in conjunction with the spatial data processing algorithms and receiving as an input an objective function set for the use by resource and constraint sets, the objective functions operating in the interactive logic allowing maximizing water withdrawal capability in the most economically efficient manner by multiple users while avoiding reduction of river water level below a predetermined minimum from overdraw conditions and the constraint sets include response of the river level modeled from static data including historical transmissivity, T, and storativity, S;

said control module receiving data monitored by the sensor suites;

said control module comparing the received data to the constraint sets;

a report/alarm responsive to said control module for action upon exceeding a threshold of any element of the objective function set;

said control module providing automatic adjustment of pumping rates, q, wherein