Method and system for optimizing logistical operations in land seismic surveys
First Claim
1. A method for modeling and optimizing logistical operations problems in land seismic survey operations, in a computer program running on a computer processor, the method comprising the steps of:
- a. formulating a logistical problem with a set of decision variables and problem data;
b. modeling the problem as an objective function and a set of constraints expressed in terms of the problem data and the decision variables; and
c. solving the objective function and generating an optimal solution for the set of decision variables to optimize the logistical problem.
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Abstract
A system and method for optimizing logistical operations in land seismic surveys. The system and method for modeling and optimizing logistical operations problems in land seismic survey operations is implemented in a computer program running on a computer processor. A logistical problem is formulated with a set of decision variables and problem data and the problem is modeled as an objective function and a set of constraints, expressed in terms of the problem data and the decision variables. The objective function is solved subject to the constraints and an optimal solution is generated for the set of decision variables to optimize the logistical problem. Logistical problems that may be optimized using this approach include: minimization of total costs in the design and operations of a land seismic survey, routing of one or more source crews through a sequence of source location points, placement of recording stations in a survey, placement of source locations, source crew and vehicle routing, offsetting source locations from exclusion zones to avoid obstacles and determining the optimal amount of an expendable resource needed for the survey.
107 Citations
39 Claims
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1. A method for modeling and optimizing logistical operations problems in land seismic survey operations, in a computer program running on a computer processor, the method comprising the steps of:
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a. formulating a logistical problem with a set of decision variables and problem data;
b. modeling the problem as an objective function and a set of constraints expressed in terms of the problem data and the decision variables; and
c. solving the objective function and generating an optimal solution for the set of decision variables to optimize the logistical problem.
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2. A method for modeling and optimizing logistical operations problems in land seismic survey operations, in a computer program running on a computer processor, the method comprising the steps of:
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a. identifying decision variables under the control of a user for a logistical problem;
b. identifying geophysical and operational constraints for the logistical problem;
c. identifying variable logistical problem parameters;
d. building a mathematical model of the logistical problem, the model being expressed as an objective function and a set of constraints in terms of the decision variables and problem parameters; and
e. generating an optimal logistical problem solution. - View Dependent Claims (3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
a. translating the mathematical model into a form suitable for solution by a solver software program; and
b. in the generating an optimal logistical problem solution step, using the solver software program to solve for the decision variables which satisfy the problem constraints and optimize the objective function.
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4. The method according to claim 3, wherein:
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a. the objective function and the set of constraints are expressed in an algebraic modeling language; and
b. the solver software program is an optimization program that optimizes the objective function.
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5. The method according to claim 2, wherein the logistical problem is a three dimensional (3D) seismic survey problem.
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6. The method according to claim 5, wherein the 3D seismic survey problem is to minimize acquisition costs in the design and operations of the 3D seismic survey.
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7. The method according to claim 6, wherein:
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a. in the identifying the decision variables step, the decision variables identified for the 3D seismic survey are selected from the group consisting of;
number of shot locations, number of receiver locations, placement of shot locations, placement of receiver locations, number of active receiver lines, number of active receiver channels per line, coordination of the shot locations, and placement of equipment to receive a reflected signal; and
b. in the building a mathematical model step, the objective function and set of constraints for minimizing acquisition costs comprise the steps of;
i. modeling preparation costs;
ii. shooting and recording costs; and
iii. modeling processing costs.
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8. The method according to claim 7, wherein the preparation costs comprise:
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a. permitting costs;
b. surveying costs;
c. cutting and clearing; and
d. drilling costs.
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9. The method according to claim 7, wherein the shooting and recording costs comprise:
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a. crew costs; and
b. equipment costs.
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10. The method according to claim 7, wherein the processing costs are a function of the size of the survey.
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11. The method according to claim 7, wherein the constraints comprise:
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a. the geophysical requirements of fold, offset and azimuth;
b. maximum number of shots per day; and
c. maximum number of channels.
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12. The method according to claim 2, wherein the logistical problem is routing a 3D seismic survey source crew through a plurality of nodes in a minimum period of time.
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13. The method according to claim 12, wherein each node represents a rack which is a set of source locations on the same source line between two adjacent receiver lines.
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14. The method according to claim 13, further comprising:
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a. identifying as decision variables the number of times the source crew passes from one node to another node;
b. requiring the constraint that each node must be visited at least once; and
c. requiring the constraint that each n ode must be departed at least once; and
d. requiring the constraint that the number of visits and departures from a node must be equal.
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15. The method according to claim 14, further comprising routing a plurality of source crews method the plurality of nodes.
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16. T he method according to claim 15, further comprising:
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a. requiring the constraint that each rack must be visited at least once by one of the source crews;
b. requiring the constraint that each source crew starts at a base camp location and returns to the base camp location; and
c. minimizing the total cost of routing the plurality of source crews by solving for an optimal number of crews and their routes while equalizing the time for each source crew to be away from the base camp location.
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17. The method according to claim 2, wherein the logistical problem is placing a recording station within a field of receiver locations such that the number of times the recording station must be moved to cover the field of receiver locations is minimized.
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18. The method according to claim 17, further comprising:
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a. identifying the location of the recording station at each point in time as a decision variable; and
b. requiring the constraint that each receiver location must be listened to at least once.
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19. A system for modeling and optimizing logistical operations problems in land seismic survey operations, comprising:
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a. means for identifying decision variables under user control for a logistical problem;
b. means for identifying geophysical and operational constraints for the logistical problem;
c. means for quantifying problem parameters;
d. means for building a mathematical model of the logistical problem, the model being expressed as an objective function subject to a set of inequalities representing the constraints, the objective function and constraints being expressed in terms of the decision variables and problem parameters; and
e. means for optimizing the objective function and solving for the decision variables while satisfying the set of constraints to generate an optimal logistical problem solution. - View Dependent Claims (20)
a. means for translating the mathematical model into a form suitable for solution by a solver software program; and
b. means for using the solver software program to solve for the decision variables which satisfy the problem constraints and optimize the objective function.
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21. A computer-implemented method of modeling and optimizing logistical operations problems in land seismic survey operations, the method comprising the steps of:
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a. identifying seismic survey decision variables for a logistical problem that can be optimized;
b. determining problem parameters;
c. identifying the seismic survey operational and geophysical constraints;
d. building a mathematical model of the logistical, the model being expressed as an objective function and a set of constraints in terms of the decision variables and problem parameters;
e. translating the mathematical model into a form suitable for solution by a solver; and
f. solving the model to generate an optimal problem solution. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38)
a. routing a plurality of 3D seismic survey source crews between the plurality of nodes in a minimum period of time;
b. minimizing the total cost of the 3D seismic survey; and
c. equalizing the total amount of time each source crew is deployed during the seismic survey.
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24. The method according to claim 21, wherein the logistical operations problem is placing a recording station within a field of receiver stations such that the number of times the recording station must be moved to cover the field of receiver stations is minimized.
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25. The method according to claim 21, wherein the logistical problem is determining an amount to purchase of an expendable item needed for equipment operations such that the amount of the expendable item is sufficient for survey operation with a minimal amount of the expendable item remaining after the survey operation is complete.
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26. The method according to claim 25, wherein the expendable item is vehicle fuel.
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27. The method according to claim 21, wherein the logistical problem is placing shot locations so as to minimize the cost of the seismic survey while satisfying the operational and geophysical constraints.
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28. The method according to claim 27, wherein the constraints comprise:
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a. placing the shot locations to achieve a minimum required fold coverage;
b. placing the shot locations so the locations fall within a minimum and maximum offset; and
c. placing the shot locations so the locations fall within a minimum and maximum azimuth.
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29. The method according to claim 27, wherein the problem parameters comprise:
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a. cost of locating the shot location at a potential shot point; and
b. a set of shot locations that shoot into a bin;
c. number of the shot locations in the bin that fall into a minimum and maximum offset;
d. minimum and maximum fold coverage for the bin that fall into the minimum and maximum offset;
e. a set of shot locations for the bin that fall into a minimum and maximum azimuth; and
f. minimum and maximum fold coverage for the bin that fall into the minimum and maximum azimuth.
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30. The method according to claim 21, wherein the logistical problem is placing shot locations and determining source crew routing so as to minimize seismic survey cost while satisfying the operational and geophysical constraints.
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31. The method according to claim 30, further comprising placing the shot locations to avoid shot exclusion zones.
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32. The method according to claim 31, wherein the shot exclusion zones are problem parameters determined by a user.
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33. The method according to claim 31, wherein the shot exclusion zones are seismic survey operational and geophysical constraints.
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34. The method according to claim 30, wherein the problem parameters comprise:
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a. cost of placing the shot location at each shot point;
b. cost of a source crew traveling between the shot locations; and
c. set of possible base camp locations.
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35. The method according to claim 34, wherein the operational and geophysical constraints comprise:
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a. placing the shot locations to achieve a minimum fold coverage;
b. placing the shot locations to fall within a minimum and maximum offset;
c. placing the shot locations to fall within a minimum and maximum azimuth;
d. requiring the source crew to enter the shot location at least once;
e. requiring number of visits to and departures from the shot locations to be equal; and
f. allowing only one base camp to be selected from the set of possible base camp locations.
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36. The method according to claim 30, wherein the logistical problem further comprises placing shot locations and determining source crew routing so the shot locations are offset from an exclusion zone in a completed survey design to avoid obstacles in the survey field.
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37. The method according to claim 36, wherein the constraints comprise:
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a. determining a set of offset shot locations for each location to be avoided in the completed survey design;
b. requiring at least one source crew to enter and leave each shot location;
c. for a plurality of source crews, equalizing the length of time for each source crew to visit the shot locations;
d. placing the shot locations to achieve a minimum fold coverage;
e. placing the shot locations so the locations fall within a minimum and maximum offset;
f. placing the shot locations so the locations fall within a minimum and maximum azimuth;
g. requiring number of visits to and departures from each shot location by the source crew to be equal; and
h. allowing only one base camp to be selected from the set of possible base camp locations.
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38. The method according to claim 30, wherein the logistical problem comprises optimizing shot location, vehicle routing and receiver equipment layout operational constraints.
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39. A computer processor instructed to execute a computer program containing instructions causing a computer processor to model and optimize logistical operations problems in land seismic survey operations, the computer program comprising:
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a) means for identifying decision variables under user control for a logistical problem;
b) means for identifying geophysical and operational constraints for the logistical problem;
c) means for quantifying variable problem parameters;
d) means for building a mathematical model of the logistical problem, the model being expressed as an objective function subject to a set of inequalities representing the constraints, the objective function being expressed in terms of the decision variables and problem parameters; and
means for optimizing the objective function and solving for the decision variables while satisfying the set of constraints to generate an optimal logistical problem solution.
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Specification