# US 11,028,681 B2 · Explorative sampling of natural mineral resource deposits > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,028,681 B2 - Document ID: US11028681B2 - Status: Granted - Kind: B2 - Application number: 16/063,117 - Filed: 2016-12-16 - Published: 2019-07-25 - Granted: 2021-06-08 - Earliest claimed: 2015-12-18 - Assignees: 1789703 Ontario Ltd. - Applicants: 1789703 Ontario Ltd. - Inventors: Andrew Dasys; Nehme Bilal - Web page: https://patentgrep.com/patent/US11028681B2 ## CPC - E21B 43/30: Specific pattern of wells, e.g. optimising the spacing of wells - E21B 41/00: Equipment or details not covered by groups E21B15/00 - E21B40/00 - G01V 1/345: {Visualisation of seismic data or attributes, e.g. in 3D cubes} - 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) - G06Q 10/06375: {Prediction of business process outcome or impact based on a proposed change} - G06Q 10/067: Enterprise or organisation modelling - G06Q 50/02: Agriculture; Fishing; Forestry; Mining - E21B 7/04: Directional drilling - E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Methods and systems for improving mineral resource exploration and resource classification efficiency are provided herein. The generation and iterative, dynamic improvement of drill plans for sampling a target volume using drill holes is described. Methods and systems for the development and optimization of drill plans are able to accommodate a wide variety of constraints and targets, providing drill plans which aim to minimize the amount of explorative drilling while substantially converting unclassified sub-volumes, and in particular high-desirability sub-volumes, of the target volume to a specified or desired level while attempting to maximize targeted resource conversion efficiency. Resulting drill plans may provide a proposed collection of drill holes, defined in 3D space, penetrating the target volume which sufficiently sample a target volume while remaining within one or more specified constraints. ## Claims ### Claim 1 A computer-implemented method for improving mineral resource exploration and resource classification efficiency, said computer-implemented method comprising: defining a one or more target volumes of interest in 3D space; segmenting the one or more target volumes into sub-volumes to which one or more attributes indicating relative desirability may be assigned; and iteratively generating and improving a drill plan using an algorithmic solver executed by a processor, wherein the drill plan aims to provide an optimal or near optimal solution for drill hole distribution within the one or more target volumes such that all or nearly all the sub-volumes, or at least the sub-volumes of greatest desirability, of the one or more target volumes are sampled to a specified or desired level, including obtaining information from a drill rig to be supplied to the algorithmic solver for the iteratively generating; graphically presenting the drill plan using an interface communicatively connected to the processor, wherein the resulting drill plan comprises a collection of one or more planned drill holes which are defined in 3D space, wherein a set of operational constraints constrains the iteratively generated and improved drill plan, and wherein the sub-volumes are blocks, and the algorithmic solver aims to generate a drill plan which attempts to maximize the number of blocks sampled by the drill holes of the drill plan while minimizing the total planned drill length of the drill plan, wherein the resulting drill plan is for identifying drill holes to be drilled by drilling equipment, wherein an orientation of a drill hole of the drill plan can be recalculated in real-time to accommodate for on-site drilling limitations, and wherein the on-site drilling limitations are any one of drill site accessibility, drill hole geometry, drill hole timing limitations, a requirement for movement of the drill rig, setup availability, or any combination thereof, and wherein a completion constraint is used to identify a point at which sufficient drilling has been completed, and wherein the point at which sufficient drilling has been completed is the point at which further increase in drill hole density provides additional value which is below a specified threshold. ### Claim 2 (depends on 1) The method according to claim 1, wherein the set of operational constraints comprises a historical drill hole locations constraint, a potential drilling setup location constraint, a drilling direction constraint, a drilling dips constraint, a drilling azimuth constraint, a drilling budget constraint, a sampling requirement constraint, a drilling setup availability constraint, a constraint regarding distribution of drill holes from setups, a constraint regarding the total amount of surface ground disturbance, a topographical constraint, an environmental constraint, a constraint regarding environmental exclusion zones, a geological fault constraint, a geological contacts constraint, a geological structure constraint, or a constraint regarding existing underground workings or operations, or any combination thereof. ### Claim 3 (depends on 1) The method according to claim 1, wherein the algorithmic solver is based on a heuristic algorithm, a linear algorithm, a metaheuristic algorithm, a metaheuristic SCP algorithm, a localized random search, a modified random search, an annealing algorithm, a taboo search, or a multiple metaheuristic algorithm comprising a genetic algorithm component, a taboo search algorithm and an iterated local search algorithm. ### Claim 4 (depends on 1) The method according to claim 1, wherein the one or more attributes indicating relative desirability of a sub-volume are selected from one or more of: distance of the sub-volume from an existing drill hole; estimate variance; grade estimates; bounding of the sub-volume by site specific geological contacts, structures, or faults; or variability or uncertainty of sub-volume grade estimation or interpolation. ### Claim 5 (depends on 1) The method according to claim 1, wherein the drill plan aims to sample sub-volumes of the one or more target volumes such that a highest aggregate desirability is achieved, wherein aggregate desirability primarily considers a value of resource classification, an identification of geological features bounding the one or more target volumes, or a combination thereof. ### Claim 6 (depends on 1) The method according to claim 1, wherein the drill plan is iteratively improved by improving the global distribution of drill holes within the drill plan based on newly acquired information as drilling operations progress. ### Claim 7 (depends on 1) The method according to claim 1, wherein the specified or desired level is selected from a range spanning geological, inferred, indicated, measured resource, and probable or proven reserve. ### Claim 8 (depends on 7) The method according to claim 7, wherein the specified or desired level is at least about 60% indicated while minimizing measured. ### Claim 9 (depends on 1) The method according to claim 1, wherein the algorithmic solver aims to generate a drill plan which attempts to maximize a number of sub-volumes sampled or classified per unit of planned drill length. ### Claim 10 (depends on 1) The method according to claim 1, wherein the drill plan provides a ranking for each planned drill hole which is based on a relative value of each planned drill hole to an overall drill plan, and wherein one or more of the lowest ranked drill holes are eliminated from the drill plan. ### Claim 11 (depends on 10) The method according to claim 10, wherein the ranking includes a penalty for moving a drill hole of the drill plan away from a position at the one or more target volumes which is easily drilled, or away from a position at the one or more target volumes at which drilling equipment is already located. ### Claim 12 (depends on 10) The method according to claim 10, wherein the relative value to the drill plan of changing one or more collar locations while dynamically updating dip and dip direction is assessed. ### Claim 13 (depends on 1) The method according to claim 1, wherein the iteratively generated drill plans are scored by a resource conversion calculator, and the algorithmic solver improves a drill plan score using one or more parameters which are changed using a constraint modifier between iterations, and wherein the constraint modifier changes or flexes one or more parameters selected from a historical drill hole locations constraint, a potential drilling setup location constraint, a drilling direction constraint, a drilling dips constraint, a drilling azimuth constraint, a drilling budget constraint, a sampling requirement constraint, a drilling setup availability constraint, a constraint regarding distribution of drill holes from setups, a constraint regarding the total amount of surface ground disturbance, a topographical constraint, an environmental constraint, a constraint regarding environmental exclusion zones, a geological fault constraint, a geological contacts constraint, a geological structure constraint, or a constraint regarding existing underground workings or operations, or any combination thereof, the specified or desired level, or a combination thereof, between iterations. ### Claim 14 (depends on 13) The method according to claim 13, wherein the scoring of the drill plans includes rewarding drill plans which provide information about location of geological structures and contacts of the one or more target volumes, or rewarding drill plans which have a reasonable probability of success. ### Claim 15 (depends on 1) The method according to claim 1, wherein the method is an iterative method which is repeated using input which is based on newly acquired information obtained from drilling one or more planned drill holes from a previously generated drill plan, wherein the one or more planned drill holes from the previously generated drill plan are drill holes which have been drilled quickly but with reduced precision for geological drilling or bounding of the one or more target volumes, allowing in-fill planning, and improving the drill plan with less invested time. ### Claim 16 (depends on 1) The method according to claim 1, wherein the method further comprises: using implicit modeling to model geological contacts, faults, shells, and surfaces; and updating the implicit modeling of the one or more target volume surfaces, geological structures, geological contacts, or a combination thereof, as drill hole data is acquired, thereby dynamically identifying sub-volumes of greatest desirability to be converted from unclassified to geological, inferred, indicated, or measured, and wherein the drill plan is recalculated and the scoring of the resulting drill plan includes a reward for solutions which allow for conversion of the identified sub-volumes of greatest desirability from unclassified to inferred, indicated or measured. ### Claim 17 (depends on 1) The method according to claim 1, wherein drill holes of the drill plan are ranked based on their value to the drill plan, and this ranking is used to indicate which holes of the drill plan should be drilled first. ### Claim 18 A computer system for improving mineral resource exploration and resource classification efficiency by generation and improvement of a drill plan, said computer system comprising: a memory for storing program instructions; and a processor for executing the program instructions; wherein the program instructions comprise instructions for: defining one or more target volumes of interest in 3D space; segmenting the one or more target volumes into sub-volumes to which one or more attributes indicating relative desirability may be assigned; and iteratively generating and improving a drill plan using an algorithmic solver, wherein the drill plan aims to provide an optimal or near optimal solution for drill hole distribution within the one or more target volumes such that all or nearly all the sub-volumes, or at least the sub-volumes of greatest desirability, of the one or more target volumes are sampled to a specified or desired level, including obtaining information from a drill rig to be supplied to the algorithmic solver for the iteratively generating; wherein the resulting drill plan comprises a collection of one or more planned drill holes which are defined in 3D space, and wherein a set of operational constraints constrains the iteratively generated and improved drill plan; and wherein the computer system comprises an interface for graphically presenting the drill plan and for receiving input of user-defined target volume of interest parameters, operational constraint parameters, or a combination thereof, wherein the resulting drill plan is for identifying drill holes to be drilled by drilling equipment, wherein an orientation of a drill hole of the drill plan can be recalculated in real-time to accommodate for on-site drilling limitations, and wherein the on-site drilling limitations are any one of drill site accessibility, drill hole geometry, drill hole timing limitations, a requirement for movement of the drill rig, setup availability, or any combination thereof, and wherein a completion constraint is used to identify a point at which sufficient drilling has been completed, and wherein the point at which sufficient drilling has been completed is the point at which further increase in drill hole density provides additional value which is below a specified threshold.