Patent Description:
The embodiments disclosed herein will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings. The drawings depict primarily generalized embodiments, which embodiments will be described with additional specificity and detail in connection with the drawings in which:.

Explosives are commonly used in the mining, quarrying, and excavation industries for breaking rocks and ore. Generally, a hole, referred to as a "blasthole," is drilled in a surface, such as the ground. Explosives may then be pumped (e.g., emulsion explosives and emulsion blends) or augered (e.g., ammonium nitrate and fuel oil (ANFO) and heavy ANFO) into the blasthole. Emulsion explosives, for example, are generally transported to a job site as an emulsion matrix that is too dense to completely detonate. In general, the emulsion needs to be "sensitized" in order for the emulsion to detonate successfully. Sensitizing is often accomplished by introducing small voids into the emulsion. These voids act as hot spots for propagating detonation. These voids may be introduced by a density reducing agent, such as by blowing a gas into the emulsion and thereby forming gas bubbles, adding microspheres or other porous media, and/or injecting chemical gassing agents to react in the emulsion and thereby form gas.

For blastholes, depending upon the length or depth, detonators may be placed at the end, also referred to as the "toe," of the blasthole and at the beginning of the emulsion explosives. Often, in such situations, the top of the blasthole will not be filled with explosives, but will be filled with an inert material, referred to as "stemming," to try to keep the force of an explosion within the material surrounding the blasthole, rather than allowing explosive gases and energy to escape out of the top of the blasthole.

Systems, methods, and apparatuses for automated loading of blastholes and methods related thereto are disclosed herein. In some embodiments, the systems, methods, and apparatuses may determine target explosive properties (e.g., explosive energy) for each blasthole in a blast pattern by identifying change points in geological properties across a blasthole and/or a blast site. For example, in some embodiments, a system may identify segments within a blasthole with similar geological properties. In some embodiments, a system may identify sections or groups of blastholes with similar geological properties by identifying change points across a distance of the blast pattern, and control a flow rate of an energy-modulating agent to a mixer to deliver an explosive with a target explosive energy value to the blasthole.

It will be readily understood that the components of the embodiments as generally described below and illustrated in the Figures herein could be arranged and designed in a wide variety of different configurations. For instance, the steps of a method do not necessarily need to be executed in any specific order, or even sequentially, nor do the steps need to be executed only once. Thus, the following more detailed description of various embodiments, as described below and represented in the Figures, is not intended to limit the scope of the disclosure, but is merely representative of various embodiments.

The phrases "operably connected to" and "connected to" refer to any form of interaction between two or more entities, including mechanical, electrical, magnetic, electromagnetic, fluidic, and thermal interaction. Two entities may interact with each other even though they are not in direct contact with each other. For example, two entities may interact with each other indirectly through an intermediate entity.

The term "proximal" is used herein to refer to "near" or "at" the object disclosed. For example, "proximal the outlet of the delivery conduit" refers to near or at the outlet of the delivery conduit.

The phrase "change point" refers to a statistically significant change point in the data. Thus, change points within a geologic profile, such as a hardness profile are statistically significant changes in the geologic values in the geologic profile.

Embodiments and implementations of the explosive delivery systems and methods described herein may include various steps, which may be embodied in machine-executable instructions to be executed by a computer system. A computer system may include one or more general-purpose or special-purpose computers (or other electronic devices). The computer system may include hardware components that include specific logic for performing the steps or may include a combination of hardware, software, and/or firmware.

Embodiments may be provided as a computer program product including a computer-readable medium having stored thereon instructions that may be used to program a computer system or other electronic device to perform the processes described herein. The computer-readable medium may include, but is not limited to: hard drives, floppy diskettes, optical disks, CD-ROMs, DVD-ROMs, ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards, solid-state memory devices, or other types of media/computer-readable media suitable for storing electronic instructions.

Computer systems and the computers in a computer system may be connected via a network. Suitable networks for configuration and/or use as described herein include one or more local area networks, wide area networks, metropolitan area networks, and/or Internet or IP networks, such as the World Wide Web, a private Internet, a secure Internet, a value-added network, a virtual private network, an extranet, an intranet, or even stand-alone machines which communicate with other machines by physical transport of media. In particular, a suitable network may be formed from parts or entireties of two or more other networks, including networks using disparate hardware and network communication technologies.

One suitable network includes a server and several clients; other suitable networks may contain other combinations of servers, clients, and/or peer-to-peer nodes, and a given computer system may function both as a client and as a server. Each network includes at least two computers or computer systems, such as the server and/or clients. A computer system may include a workstation, laptop computer, disconnectable mobile computer, server, mainframe, cluster, so-called "network computer" or "thin client," tablet, smart phone, personal digital assistant or other hand-held computing device, "smart" consumer electronics device or appliance, medical device, or a combination thereof.

Suitable networks may include communications or networking software, such as the software available from Novell®, Microsoft®, and other vendors, and may operate using TCP/IP, SPX, IPX, and other protocols over twisted pair, coaxial, or optical fiber cables; telephone lines; radio waves; satellites; microwave relays; modulated AC power lines; physical media transfer; and/or other data transmission "wires" known to those of skill in the art. The network may encompass smaller networks and/or be connectable to other networks through a gateway or similar mechanism.

Each computer system includes one or more processors and/or memory; computer systems may also include various input devices and/or output devices. The processor may include a general-purpose device, such as an Intel®, AMD®, or other "off-the-shelf" microprocessor. The processor may include a special-purpose processing device, such as an ASIC, SoC, SiP, FPGA, PAL, PLA, FPLA, PLD, or other customized or programmable device. The memory may include static RAM, dynamic RAM, flash memory, one or more flip-flops, ROM, CD-ROM, disk, tape, magnetic, optical, or other computer storage medium. The input device(s) may include a keyboard, mouse, touch screen, light pen, tablet, microphone, sensor, or other hardware with accompanying firmware and/or software. The output device(s) may include a monitor or other display, printer, speech or text synthesizer, switch, signal line, or other hardware with accompanying firmware and/or software.

The computer systems may be capable of using a floppy drive, tape drive, optical drive, magneto-optical drive, or other means to read a storage medium. A suitable storage medium includes a magnetic, optical, or other computer-readable storage device having a specific physical configuration. Suitable storage devices include floppy disks, hard disks, tape, CD-ROMs, DVDs, PROMs, RAM, flash memory, and other computer system storage devices. The physical configuration represents data and instructions which cause the computer system to operate in a specific and predefined manner as described herein.

Suitable software to assist in implementing the invention is readily provided by those of skill in the pertinent art(s) using the teachings presented here and programming languages and tools, such as Java, Pascal, C++, C, PHP,. Net, database languages, APIs, SDKs, assembly, firmware, microcode, and/or other languages and tools. Suitable signal formats may be embodied in analog or digital form, with or without error detection and/or correction bits, packet headers, network addresses in a specific format, and/or other supporting data readily provided by those of skill in the pertinent art(s).

Aspects of certain embodiments may be implemented as software modules or components. As used herein, a software module or component may include any type of computer instruction or computer executable code located within or on a computer-readable storage medium. A software module may, for instance, comprise one or more physical or logical blocks of computer instructions, which may be organized as a routine, program, object, component, data structure, etc., that performs one or more tasks or implement particular abstract data types. A particular software module may comprise disparate instructions stored in different locations of a computer-readable storage medium, which together implement the described functionality of the module. Indeed, a module may comprise a single instruction or many instructions, and may be distributed over several different code segments, among different programs, and across several computer-readable storage media.

Some embodiments may be practiced in a distributed computing environment where tasks are performed by a remote processing device linked through a communications network. In a distributed computing environment, software modules may be located in local and/or remote computer-readable storage media. In addition, data being tied or rendered together in a database record may be resident in the same computer-readable storage medium, or across several computer-readable storage media, and may be linked together in fields of a record in a database across a network. According to one embodiment, a database management system (DBMS) allows users to interact with one or more databases and provides access to the data contained in the databases.

An explosives delivery system comprises a first reservoir configured to store an energy-modulating agent, such as a density-reducing agent. The system also comprises a second reservoir configured to store an energetic substance, such as an emulsion matrix, and a mixer configured to combine the energetic substance and the energy-modulating agent into an explosive, such as an emulsion explosive. The mixer is operably connected to the first reservoir and the second reservoir. A delivery device, such as a delivery conduit, is operably connected to the mixer, the first reservoir, and the second reservoir, and configured to convey the explosive into a blasthole.

The explosives delivery system comprises processor circuitry to receive dimensions of the blasthole. The processor circuitry may determine change points within a geologic profile, where the geologic profile may include hardness values representing geological characteristics, such as hardness, along the length of the blasthole. The processor circuitry may segment the blasthole into groups separated by the change points. Additionally, the processor circuitry may determine a representative hardness value for each group. Additionally, the processor circuitry may determine a target explosive energy value for each group based on the representative hardness value, thereby generating a target explosive energy profile comprising target explosive energy values along the length of the blasthole. The system may control a flow rate of the energy-modulating agent, such as a density-reducing agent, to the mixer to vary the energy of the explosive as needed according to the target explosive energy profile.

In some embodiments of methods of delivering explosives, the methods comprise receiving dimensions of the blasthole. The methods further comprise determining any change points within a geologic profile, wherein the geologic profile comprises geologic data such as hardness values representing geologic hardness characteristics along a length of the blasthole. The methods further comprise segmenting the blasthole into one or more groups separated by the change points. The methods may further comprise determining a representative hardness value for each group. The methods further comprise determining a target explosive energy value, such as a target emulsion density value, for each group of the one or more groups based on the representative hardness value. The methods further comprise mixing an energetic substance (e.g., an emulsion matrix) and the energy-modulating agent (e.g., a density-reducing agent) into an explosive. The method further comprises controlling a flow rate of the energy-modulating agent to achieve the target explosive energy for each group.

Methods of determining an emulsion explosive density profile for a blasthole not covered by the claims are also disclosed herein. In some embodiments, the methods comprise determining any change points within a geologic profile, wherein the geologic profile comprises geologic data such as hardness values representing hardness characteristics along a length of the blasthole. The methods may further comprise segmenting the blasthole into one or more groups separated by any identified change points. The methods may further comprise determining a representative hardness value within each group. The methods may further comprise determining a target emulsion density for each group based on the representative hardness value for each group, thereby generating a target density profile comprising target emulsion density values along the length of the blasthole.

Non-transitory computer-readable media are also disclosed herein. In some embodiments, the media comprise instructions to cause, upon execution of the instructions by one or more processors, an explosive delivery system to receive dimensions of a blasthole and determine any change points within a geologic profile, wherein the geologic profile comprises geologic data such as hardness values representing hardness characteristics along a length of the blasthole. The media may further comprise instructions to segment the blasthole into one or more groups separated by any identified change points. The media may further comprise instructions to identify a representative hardness value within each group. The media may further comprise instructions to determine a target explosive energy or a target emulsion density for each group based on the representative hardness value, thereby generating either a target explosive energy profile or a target emulsion density profile comprising target values along the length of the blasthole.

Much of the disclosure herein is specific to emulsion explosives where the emulsion matrix is the energetic substance and the density-reducing agent is the energy-modulating agent. The disclosure herein regarding emulsion explosives is applicable to other explosives. Likewise, the disclosure herein regarding explosives generally is applicable to emulsion explosives. Emulsion explosives are one example of an explosive contemplated by this disclosure. Other examples of explosives are ANFO, heavy ANFO, and ANFO or ammonium nitrate (AN) prill blends with emulsion explosives. The systems and methods disclosed herein are applicable to a variety of explosives. For example, the energetic substance may be ANFO and an energy-modulating agent may be mixed with the ANFO in varying amounts as the ANFO is augered into the blasthole, to thereby increase or decrease the energy level of the ANFO at particular depths of the blasthole according to a target explosive energy profile. In another example, ANFO or AN prill may be the energy-modulating agent and an emulsion explosive may be the energetic substance. In this example, the emulsion explosive may be at a constant or variable density. The ANFO or AN prill may be mixed with the emulsion explosive in varying amounts as it is augered or pumped into the blasthole, to thereby increase or decrease the energy level of the explosive blend at particular depths of the blasthole according to a target explosive energy profile. One of ordinary skill in the art, with the benefit of this disclosure, would understand that a variety of energetic substances and energy-modulating agents may be used with the systems and methods disclosed herein.

Turning now to the figures, <FIG> illustrates a side view of one embodiment of a truck <NUM> equipped with an explosive delivery system <NUM> for automatically adjusting the density of an emulsion explosive for various segments in a blasthole or various blasthole groups within a blast pattern. As shown, the explosive delivery system <NUM> may include a first reservoir <NUM>, a second reservoir <NUM>, and a mixer <NUM> mounted on the truck <NUM>.

An emulsion explosive may be formed by mixing the contents of the first reservoir <NUM> and the second reservoir <NUM>. The first reservoir <NUM> may store a density-reducing agent. The second reservoir <NUM> stores an emulsion matrix. The mixer <NUM> is operably connected to the first reservoir <NUM> and the second reservoir <NUM>. The mixer <NUM> combines the density-reducing agent and the emulsion matrix into an emulsion explosive. In some embodiments, the density-reducing agent comprises a chemical gassing agent.

The mixer <NUM> may combine the density-reducing agent and the emulsion matrix at one or more places. In some embodiments, the mixer <NUM> may combine the density-reducing agent and the emulsion matrix on the truck <NUM>, in a delivery conduit <NUM>, and/or in a blasthole <NUM>. In some embodiments, the delivery conduit <NUM> is indirectly connected to the first reservoir <NUM> and second reservoir <NUM>. For example, as shown, the mixer <NUM> may connect the delivery conduit <NUM>, the first reservoir <NUM> and the second reservoir <NUM>. In this arrangement, the mixer <NUM> may produce an emulsion explosive <NUM> on the truck <NUM>. In some embodiments, the delivery conduit <NUM> is configured to introduce the density-reducing agent to the emulsion matrix proximal an inlet of the mixer when the mixer is located in the nozzle <NUM>.

In some embodiments, the mixer <NUM> may produce the emulsion explosive <NUM> within the blasthole <NUM>. For example, the mixer may be located in a nozzle <NUM> proximal an outlet of the delivery conduit <NUM> and the mixer <NUM> may not be present. In such embodiments, the delivery conduit <NUM> may include one tube for conveying emulsion matrix and a separate tube for conveying the density-reducing agent to the nozzle <NUM> to be combined with the emulsion matrix. In embodiments where the nozzle <NUM> is used to mix the density-reducing agent and the emulsion matrix, the density of the emulsion explosive <NUM> being conveyed into the blasthole <NUM> can be rapidly changed with precision.

The nozzle <NUM> is connected at the end of the delivery conduit <NUM>. The delivery conduit <NUM> is operably connected to the mixer <NUM>. The delivery conduit <NUM> and the nozzle <NUM> are configured to convey the emulsion explosive <NUM> into the blasthole <NUM>. The truck <NUM> is positioned near the vertical blasthole <NUM>. The delivery conduit <NUM> is unwound from a hose reel <NUM> and inserted into the vertical blasthole <NUM>.

In some embodiments, the explosive delivery system <NUM> comprises processor circuitry <NUM> to determine segments <NUM>, <NUM> within the blasthole <NUM> with different geologic hardness characteristics. The processor circuitry <NUM> may also control a flow rate of the density-reducing agent in the first reservoir <NUM> to achieve a target emulsion density based on the geologic hardness characteristics for each segment. Accordingly, the explosive delivery system <NUM> may automatically adjust the density of an emulsion explosive for the segments <NUM>, <NUM> in the blasthole <NUM>. By differentiating the segments <NUM>, <NUM> and adjusting the density of the emulsion explosive <NUM> within each segment <NUM>, <NUM>, blasting can be tailored to the geologic properties of the particular blasthole and dig rates and mill productivity can be increased thereby.

In some embodiments, the processor circuitry <NUM> may determine that a first emulsion explosive group at a first density has been delivered to the blasthole <NUM> and that a second emulsion explosive group at a second density is to be delivered to the blasthole <NUM>. For example, the processor circuitry <NUM> may determine that a sufficient volume of explosive to fill a particular length or depth of the blasthole <NUM> has been achieved. The processor circuitry <NUM> may then modify the flow rate of the density-reducing agent such that the emulsion explosive <NUM> delivered by the delivery conduit <NUM> has the target emulsion density associated with the second emulsion explosive group.

For example, the processor circuitry <NUM> may monitor a delivery rate of the emulsion matrix to determine, based on the dimensions of the blasthole <NUM> and the expansion of the emulsion matrix due to gassing (i.e., formation of the emulsion explosive), a current group of the blasthole <NUM> being filled. In some embodiments, the depth of the delivery conduit <NUM> may be based on the amount of delivery conduit <NUM> on the hose reel <NUM>.

When the processor circuitry <NUM> determines that a second emulsion explosive group at a second density is to be delivered to the blasthole <NUM>, the processor circuitry <NUM> may modify the flow rate of the density-reducing agent such that the emulsion explosive <NUM> delivered by the delivery conduit <NUM> has the target emulsion density associated with the second emulsion explosive group. For instance, the processor circuitry <NUM> may send a signal to the mixer <NUM> to increase the amount of the density-reducing agent or to reduce the density of the emulsion explosive <NUM>.

In some embodiments, the explosive delivery system <NUM> may comprise a memory storage device <NUM>. The memory storage device <NUM> may store a table comprising target emulsion densities for a plurality of hardness values. In some embodiments, to determine the target emulsion density for each group, the processor circuitry <NUM> accesses the table and locates a target emulsion density based on the representative hardness value identified for each group.

The processor circuitry <NUM> may receive more detailed information about each of the blastholes including the geologic profile. In some embodiments, the processor circuitry <NUM> generates a geologic profile based on one or more types of geologic data. Non-limiting examples of geologic data include mineralogy (elemental and/or mineral), lithologic structure (primary, secondary, and/or texture), porosity, hardness, rock strength, and density. "Texture" refers to the size, shape, and arrangement of the interlocking mineral crystals which form a rock or other material. The geologic data may be used to determine further geologic characteristics, such as friability and fragmentability. The geologic data may be determined directly or indirectly from sources such as seismic data, drilling data, drill cuttings, core samples, or combinations thereof. For example, drill cuttings and/or core samples may be analyzed using x-ray or gamma-ray fluorescence, scanning electron microscopy, and other spectroscopy and/or microscopy techniques. The geologic data may include information on an incremental basis, such as on a per foot basis.

In the case of drilling data, the processor circuitry <NUM> may receive drilling data, a diameter of the blasthole <NUM>, and the length of the blasthole <NUM>. The drilling data may include information on an incremental basis, such as, on a per foot basis. The drilling data may include information such as drill bit size, drill bit rotary speed, drill bit torque, penetration rate, bit vibration, pull down pressure, bailing air pressure, hole location, hole number, and hole length or depth. The drilling data may correlate to the geologic properties along the length of the blasthole. Thus, drilling data can be used to generate hardness values along the length of the blasthole (i.e., the hardness profile). For example, the processor circuitry <NUM> may receive the drill data and generate the hardness profile or may receive the hardness profile from another system that generated the hardness profile from the drilling data. The processor circuitry <NUM> may receive drilling data directly from one or more drill rigs or from a separate source that has received the drilling data. The processor circuitry may also receive the hardness profile and dimensions of the blasthole, instead of receiving the drilling data.

In the case of seismic data, the processor circuitry <NUM> may receive data from one or more geophones or other seismic sensors. The geophones may record vibration during drilling and/or from test charges. The processor circuitry <NUM> may compare seismic vibration at a source (e.g., the drill or test charge) and seismic vibrations at the one or more geophones. Based at least on the delay, frequency, and amplitude of the seismic vibrations, the processor circuitry <NUM> may determine geologic properties (e.g., fragmentation, composite densities, compositions, rock impedances, hardness value, Young's modulus, shear strain, or other such properties).

In some embodiments, the processor circuitry <NUM> may determine an energy profile comprising a target explosive energy for one or more groups of blastholes, and a processor on the truck <NUM> to deliver the explosive according to the energy profile.

In some embodiments, the processor circuitry <NUM> receives a blast pattern comprising location data of a plurality of blastholes, and geologic values associated with the plurality of blastholes. The geologic values represent geologic characteristics of the plurality of blastholes. In some embodiments, the geologic values comprise an average geologic value for each of the plurality of blastholes. For example, when the geologic values include hardness values, then the hardness value may be an average hardness value for each of the plurality of blastholes.

The processing circuitry <NUM> may determine any change points in the geologic values along a distance of the blast pattern. The distance of the blast pattern where the processor circuitry is to determine any change points in the geologic values may be a row or a line of holes in a burden direction. In some embodiments, change points may be determined in both spacing and burden directions of a blast pattern. In some embodiments, change points may be determined row by row. In some embodiments, an anchor blasthole may be used as a starting location, and change points are determined across a line in the blast plan at a plurality of angles.

In some embodiments, the processing circuitry <NUM> can determine segment changes by using a lookup table where material type, average hardness and hole diameter (as an example) could be used to provide a loading profile for each hole. The loading profiles could be applied on a hole by hole basis.

The processing circuitry <NUM> may segment the blast pattern into one or more groups of blastholes separated by any identified change points. Additionally, the processing circuitry <NUM> may determine a target explosive energy for each group of blastholes based on a representative geologic value for each group of blastholes, thereby generating a target energy profile comprising target explosive energy values for each blasthole in the plurality of blastholes. In some embodiments, an available amount of explosive material is used to determine the target explosive energy for each group. The processing circuitry <NUM> may control a flow rate of the energy-modulating agent to the mixer to deliver, via the delivery device, the explosive with a target explosive energy value to the blasthole <NUM> according to the target energy profile.

Alternatively, the processor circuitry <NUM> can determine segment changes based on other methods. For example, when three segments are desired, the blastholes can be separated numerically into a low hardness category, a medium hardness category, and a high hardness category. In that example, blastholes in the first segment, the low hardness category, might be filled with ANFO and a bulking agent, to reduce the energy of the ANFO. The blastholes in the second segment, the medium hardness category, might be filled with ANFO. The blastholes in the third segment, the high hardness category, might be filled with heavy ANFO.

<FIG> illustrates a flow chart of one embodiment of a method <NUM> of delivering explosives. The method <NUM> described with reference to <FIG> may be executed by processor circuitry, such as the processor circuitry <NUM> of <FIG>.

In this embodiment, the method <NUM> comprises receiving <NUM> a geologic profile. The geologic profile may include geologic values representing one or more geologic characteristics of the plurality of blastholes in the blast plan. In some embodiments, the method includes receiving drilling data comprising geologic hardness characteristics, a diameter of the blasthole, and a length of the blasthole. This information may be provided directly by data received during a drilling operation, or may be operator entered. In some embodiments, the method includes receiving seismic data. In some embodiments, the method <NUM> includes generating a hardness profile based on drilling data and/or seismic data.

The method <NUM> further includes determining <NUM> any change points also sometimes referred to as inflection points within the geologic profile. In some embodiments, the method determines <NUM> change points across the coordinates of the plurality of blastholes in the blast plan (e.g., <FIG> and <FIG>). In some embodiments, the method determines <NUM> change points within a blasthole (e.g., <FIG>).

See <FIG> for an illustration of how one embodiment finds change points within the geologic profile. In some geologic profiles there are no change points. This results in a single target emulsion density to be used for an entire blast plan. In other geologic profiles there are one or more change points, such as multiple change points resulting in multiple groups with one or more different target emulsion densities. For example, the change points may be determined using a sequential analysis technique, such as a cumulative sum technique, or other techniques that determine the confidence level of a change in momentum in a data series.

In some embodiments, the emulsion density may be varied within a blasthole. For example, a user may preselect a desired profile for blast holes in a blast pattern. The profile may be unique to each blasthole, may apply to all blast holes, or a group of blastholes. Thus the energy distribution within each hole may vary based on the preselected profile.

It should be understood that the disclosed methods of varying the explosive energy of explosives in a blasthole may be used to implement any number of desired explosive energy profiles of the sensitized product. For example, it may be desirable to have a lower density explosive at a top of a blasthole and a higher density explosive at a bottom of a blasthole. For example, the energy distribution of a blasthole may be roughly pyramidal. In another example, the energy profile may have a higher density explosive at the top of the blasthole. The resulting energy distribution of the blasthole may be an inverted pyramid. In yet another example, the explosive near a middle section of the blasthole may have a higher density than the top or the bottom, resulting in a convex shaped energy distribution.

The method <NUM> further includes segmenting <NUM> the geologic profile into one or more groups separated by any identified change points. The groups may be vertical segments within a blasthole and/or groups of blastholes across the coordinates of a blast plan. The method <NUM> further includes determining <NUM> a representative geologic value for each group. The representative geologic value may be defined by a probability distribution, an average geologic value, a maximum geologic value, or a minimum geologic value for a particular group. Examples of a probability distribution include the mean, median, or mode of the geologic values for a particular group.

The method <NUM> further includes determining <NUM> a target explosive energy value, such as a target emulsion density, for each group based on the representative geologic value for each group, thereby generating a target explosive energy profile comprising target explosive energy values for each segment. In some embodiments, determining the target explosive energy value for each group comprises accessing a table and locating the target explosive energy value based on the representative geologic value associated with each group. The table can include target explosive energy values for a plurality of geologic values.

The target explosive energy values may be found from an algorithm, based on previous experience, or a combination thereof. For example, in embodiments where an algorithm is used to generate the hardness profile from drilling data and/or seismic data, the hardness values generated may be relative values, not absolute values. When relative values are generated, then it may be beneficial to conduct one or more test charges in the blast site and compare the performance of different target explosive energy values at particular hardness values within the test blastholes. For example, in such a manner, the target emulsion densities correlated with particular hardness values can be fine-tuned. Or stated another way, the output of the algorithm used to generate the hardness profile can be fine-tuned with one or more test blasts. Thus, the target emulsion densities generate a target density profile comprising target emulsion density values along the length of the blasthole. The target energy profile, such as a target density profile, may be modified with a stemming length, an air decking location and length, other regions devoid of emulsion explosive, or combinations thereof.

Test blasts and/or previous blasts may be used to fine-tune the target energy profile to obtain a desired fragmentation size. Feedback from the test blasts and/or previous blasts may include fragmentation size data from a mill analysis, a muck pile analysis, or a conveyor analysis. The method <NUM> may include changing emulsion densities associated with hardness values to optimize future blasts based on the feedback. For example, the future blast may have an optimized fragmentation size based on the feedback. Optimizing future fragmentation size may include adjusting the target energy profile to alter the fragmentation size so that the fragments are closer to a target or desired size. For example, a system may alter the values of a lookup table that the system uses to determine target explosive values. For instance, if the table includes target explosive energy values for a plurality of geologic values, the system may use the feedback to alter the target explosive energy values, the plurality of geologic values, or both. For example, the outputs of the algorithm used to generate the geologic values and/or the geologic profile can be fine-tuned so as to achieve a desired fragmentation size. In some embodiments, the method <NUM> may alter the geologic values for a group based on the feedback. In some embodiments, the method <NUM> may alter the segmentation based on the feedback. In some embodiments, the method <NUM> may alter one or more of the lookup table, the geologic values for a group, and the segmentation based on the feedback.

The method <NUM> may further include controlling <NUM> a flow rate of the energy-modulating agent to the mixer to achieve the target explosive energy value for the blasthole being filled.

The method <NUM> may further include the operator confirming or inputting the depth of any water present in the blasthole. The target emulsion density for explosives in contact with water may be automatically increased to greater than <NUM>/cm<NUM>, if the target emulsion density for the group was not already greater than <NUM>/cm<NUM>.

In some embodiments, only a portion of the steps of the method <NUM> may be performed. For example, when the geologic profile is generated, rather than received, then step <NUM> may not be performed. In yet another example, in some embodiments only steps <NUM>-<NUM> may be performed. Additionally, in some embodiments, some of the steps of the method <NUM> may be combined together into a single step.

<FIG> illustrates a flow chart of one embodiment of a method <NUM> of delivering explosives with varying target explosive energy within a blasthole. The method <NUM> may segment a blasthole and determine a target emulsion density for each section of the blasthole. The method <NUM> described with reference to <FIG> may be executed by processor circuitry, such as the processor circuitry <NUM> of <FIG>.

In this embodiment, the method <NUM> comprises receiving <NUM> a geologic profile and dimensions of the blasthole. The geologic profile may include hardness values or other geologic values representing one or more geologic characteristics along the depth of the blasthole. In some embodiments, the method includes receiving drilling data comprising geologic hardness characteristics, a diameter of the blasthole, and a length of the blasthole. This information may be provided directly by data received during a drilling operation, or may be operator entered. In some embodiments, the method <NUM> includes receiving seismic data. In some embodiments, the method <NUM> includes generating a hardness profile based on drilling data and/or seismic data.

The method <NUM> further includes determining <NUM> any change points also sometimes referred to as inflection points within the geologic profile. See <FIG> for an illustration of how one embodiment finds change points within the geologic profile. In some geologic profiles there are no change points. This results in a single target emulsion density to be used for an entire blasthole. In other geologic profiles there are one or more change points, such as multiple change points resulting in multiple groups with one or more different target emulsion densities. For example, the change points may be determined using a sequential analysis technique, such as a cumulative sum technique, or other techniques that determine the confidence level of a change in momentum in a data series.

The method <NUM> further includes segmenting <NUM> the blasthole into groups separated by the change points. The number of segments may be limited by physical parameters of the blasthole and/or explosive delivery system. For example, a maximum number of supported segments may be based on parameters of the blasthole, flow rate of delivery system equipment and/or limitations or responsiveness of the control system for the delivery system equipment. In some embodiments, the control system for the delivery system equipment may only allow a certain number of density changes, such as, for example, four, six, or eight density changes (which equates to four, six, or eight segments in the blasthole). The parameters of the blasthole may include a stemming depth, a blasthole length, and a blasthole diameter. The method <NUM> may include determining a maximum number of density changes achievable by the delivery system equipment, the control system, or both. The method <NUM> may include removing segments or potions of segments to be occupied by stemming, air decking, other regions devoid of emulsion explosive, or combinations thereof. For example, an operator may be able to input into a user interface the stemming length and any air decking location and length, and the processor circuitry can modify the segments accordingly. The processor circuitry may also receive that information in other ways.

The method <NUM> further includes determining <NUM> a representative geologic value for each group. The representative geologic value may be defined by a probability distribution, a maximum geologic value, or a minimum geologic value for a particular group. Examples of a probability distribution include the mean, median, or mode of the geologic values for a particular group.

The method <NUM> further includes determining <NUM> a target explosive energy value, such as a target emulsion density, for each group based on the representative geologic value for each group. In some embodiments, determining the target explosive energy value for each group comprises accessing a table and locating the target explosive energy value based on the representative geologic value associated with each group. The table can include target explosive energy values for a plurality of geologic values. The target explosive energy values may be found from an algorithm, based on previous experience, or a combination thereof. For example, in embodiments where an algorithm is used to generate the geologic profile from drilling data and/or seismic data, the geologic values generated may be relative values, not absolute values. When relative values are generated, then it may be beneficial to conduct one or more test charges in the blast site and compare the performance of different target explosive energy values at particular geologic values within the test blastholes. For example, in such a manner, the target emulsion densities correlated with particular geologic values can be fine-tuned. Or stated another way, the output of the algorithm used to generate the geologic profile can be fine-tuned with one or more test blasts. Thus, the target emulsion densities generate a target density profile comprising target emulsion density values along the length of the blasthole. The target energy profile, such as a target density profile, may be modified with a stemming length, an air decking location and length, other regions devoid of emulsion explosive, or combinations thereof.

The method <NUM> may further include monitoring <NUM> a level of the explosive in the blasthole. For example, the method <NUM> may determine a current group based on the volume of explosive that has be delivered to the blasthole and the known geometry of the blasthole. The method <NUM> may determine that a current group has been filled and a new group is to be filled.

The method <NUM> may further include controlling <NUM> a flow rate of the energy-modulating agent to the mixer to achieve the target explosive energy value for the group at the level of the explosive. For example, when a change point is passed, the method <NUM> may adjust the explosive to the target explosive energy value associated with the new group, such as by adjusting the density of the explosive when the explosive contains an emulsion explosive.

Additionally, the operator can confirm or modify the length of the blasthole associated with the geologic profile, based on the actual length of the blasthole, as compared to the length of the blasthole as recorded during drilling. The method <NUM> may include modifying the length of the last group or the first group to accommodate for deviations between the blasthole length associated with the geologic profile and the actual blasthole length.

<FIG> illustrates a flow chart of one embodiment of a method <NUM> of determining change points of a geologic profile, exemplified for a hardness profile, of a blasthole. The method <NUM> described with reference to <FIG> may be executed by processor circuitry, such as the processor circuitry <NUM> of <FIG>. Using a cumulative summation approach, the processing circuitry can perform an iterative analysis on a hardness profile and compare the cumulative difference for each iteration to random "noise. " Based on the noise comparison, a confidence level for possible change points can be found. The process can be iteratively repeated on subsets of hardness values to identify any additional change points.

The hardness values may be included with data generated from drilling a blasthole, may be generated from drilling data, may be generated from seismic data, or may be independently received by the processor circuitry <NUM>.

The method <NUM> may include calculating <NUM> a cumulative difference between actual hardness values and a mean of the hardness values for the blasthole. The hardness profile may include hardness values on an incremental basis, such as a per-foot basis. When the incremental basis is consistent, then each increment can be treated as a segment for cumulative sum purposes. The cumulative difference (Sx) may be found by summing the prior segments' cumulative difference (Sx-<NUM>) and the difference between the current segment hardness (H<NUM>) and the mean hardness (mH) of the set of hardness values, such that:
<MAT>.

Equation <NUM> may be applied sequentially to each segment. Using this specific cumulative sum approach, the first cumulative difference (S<NUM>) and the last cumulative data point are always going to be zero.

The method <NUM> may further determine <NUM> a first peak value of the cumulative difference. Methods of determining peak values (which can be positive or negative) can include plotting the value of each difference. Any changes in direction in the plotted cumulative difference represent a change, or a potential change point, in the hardness profile. Other mathematical approaches may be used for determining changes in direction in the data.

Next, the change in direction may be evaluated to determine whether the change is statistically significant. Therefore, the processing circuitry may test the possible change point to see if it is just noise or there is actually a quantifiable change in mean.

The method <NUM> may further include comparing <NUM> the first peak value to statistical noise in the actual hardness values and identifying the first peak value as a change point if the first peak value exceeds statistical noise. For example, in one embodiment, the method <NUM> randomizes the actual hardness values to generate a plurality of randomly ordered hardness profiles. The method <NUM> may then calculate a cumulative difference and peak value for each of the plurality of randomly ordered hardness profiles. The method <NUM> may compare these random peak values to the first peak value to determine the percentage of random peak values that exceed the first peak value.

The method <NUM> may use the comparison between the first peak value and statistical noise to determine <NUM> a confidence level. The confidence level may provide insight to whether the first peak value is a change point. In the illustrated embodiment, the confidence level is compared <NUM> to a threshold confidence value. The method identifies <NUM> the first peak value as a change point if the percentage of random peak values that exceed the first peak value is less than a selected confidence value. For example, the threshold may be set to <NUM>%, and if the percentage of random peak values that exceed the first peak value is less than <NUM>% the point is identified as a change point. The threshold confidence value is a parameter that may be set by a user, such as via processing circuitry.

The method <NUM> may iterate the steps on a subset of the hardness values. The subset may include values between previously identified change points and blasthole boundaries. Thus, the method <NUM> may identify any additional change points by iteratively determining additional peak values of portions of the hardness values bounded by one or more previously determined change points and comparing each of the additional peak values to statistical noise in the relevant portions of the actual hardness values, and identifying each of the additional peak values as a change point if each of the additional peak values exceeds statistical noise. The iterative process may continue until peak values for that subset of data no longer yield change points or until a maximum number of segments is reached.

In some embodiments, a change point may be discarded, even though it has a sufficiently high confidence level, if the change point is too close to an already identified change point. For example, if the previously identified, but too close, change point had a higher confidence level than the later identified change point, then the later identified change point may be discarded. Likewise, if the later identified, but too close, change point had a higher confidence level than the previously identified change point, it may be discarded. The minimum distance between change points may be a user set parameter or may be determined by processing circuitry, based on factors such as responsiveness of the equipment and/or control system to changes in process control values (e.g., changes in the flow rate of a chemical gassing agent).

In some embodiments, the processing circuitry may be configured to determine all change points in a blasthole. In scenarios where more change points are identified than can be utilized, then the change points can be ranked by confidence level and the change points with the highest confidence levels utilized. For example, when a system is limited to six different segments that can be delivered to a blasthole, but more than five change points are identified, then the five change points with the highest confidence levels would be utilized.

In some situations, no change point will be identified in the blasthole. In these situations, a single target emulsion density is used for the blasthole. In other situations multiple change points will be identified. In these situations, multiple groups with different target emulsion densities will be identified.

<FIG> illustrate the results of a specific embodiment of the method <NUM> of <FIG> applied to an example hardness profile <NUM>. It should be understood that the method <NUM> may be applied to any geologic value, not just hardness values.

Processor circuitry, such as the processor circuitry <NUM> of <FIG>, could receive the hardness profile <NUM> and identify any change points via the method <NUM> of <FIG>.

Specifically, <FIG> illustrates an example hardness profile <NUM> plotted for a blasthole.

<FIG> illustrates a cumulative difference <NUM> for the hardness profile <NUM> plotted with random noise <NUM>. A peak <NUM> of the cumulative difference <NUM> indicates that there was a change point at that point in the blasthole. The random noise <NUM> was used to provide confidence that the peak <NUM> represented a change point.

The cumulative difference (Sx) was found by summing the prior segments cumulative difference (Sx-<NUM>) and the difference between the current segment hardness (H<NUM>) and the mean hardness (mH) of the set of hardness values, such that:
<MAT>.

The mean hardness for the example hardness profile <NUM> of <FIG> is <NUM>. Using this specific cumulative sum approach, the first cumulative difference (S<NUM>) and the last cumulative data point were set to be zero. Applying Equation <NUM> to the hardness profile <NUM> of <FIG> results in: <MAT> <MAT> <MAT>.

The graph <NUM> plots the value of each sample along the y-axis. The x-axis represents the sample number. As the graph <NUM> shows, the plotted cumulative difference values resulted in a graph with one very apparent change in direction (peak <NUM>). The change in direction represented a change, a potential change point, in the hardness profile.

However, the change may not be significant. To test, the random noise <NUM> was compared with the cumulative difference <NUM>.

To generate the random noise <NUM>, the order of the samples was changed to a random order. So instead of <NUM>, <NUM>, <NUM>, <NUM>. <NUM>, the sample order might be <NUM>, <NUM>, <NUM>, <NUM>, <NUM>. <NUM> or <NUM>, <NUM>, <NUM>, <NUM>. A plurality of these randomly ordered hardness profiles were created. For example, <NUM>,<NUM> random permutations of the hardness profile samples were generated. The cumulative difference for each of these randomly ordered hardness profiles was found by iteratively using Equation <NUM>.

<FIG> is a graph <NUM> of a distribution of the difference between the maximum and minimum values of the cumulative difference of the randomly ordered hardness profiles. In the illustrated example, the maximum value of the cumulative difference <NUM> of the original samples was zero. The minimum value was -<NUM>. Therefore, the difference between the maximum and the minimum values was <NUM>. The number of instances that the random data exceeds the difference of the maximum and the minimum value of the cumulative difference <NUM> reduces the likelihood there is a change point at the peak <NUM>. In <FIG>, none of the random permutations exceeded the <NUM>,<NUM> value. Therefore, there was a <NUM>% confidence that a change point occurred at sample <NUM> where the peak <NUM> was.

<FIG> illustrates the hardness profile <NUM> of <FIG> with a first change point <NUM> marked as identified by the iterative cumulative sum process discussed in <FIG>. The process used to find the first change point <NUM> was repeated on a subset of the samples.

<FIG> illustrates a cumulative difference <NUM> for segments <NUM>-<NUM> of the hardness profile of <FIG> plotted with random noise <NUM>. The random noise <NUM> was produced from the values of the same subset. A peak <NUM> of the cumulative difference <NUM> indicated that there may be a change point at that point in the blasthole. The random noise <NUM> was used to provide a confidence that the peak <NUM> represented a change point.

<FIG> is a graph <NUM> of a distribution of the difference between the maximum and minimum values of the cumulative difference of the randomly ordered hardness profiles. In the illustrated embodiment, the maximum value of the cumulative difference <NUM> of the original samples is -<NUM>. The minimum value is <NUM>. Therefore, the difference between the maximum and the minimum values is <NUM>. The number of instances that the random data exceeds the difference of the maximum and the minimum value of the cumulative difference <NUM> reduces the likelihood there is a change point and the peak <NUM>. In <FIG>, only <NUM>% of the random permutations exceeded the <NUM> value. Therefore, there was a <NUM>% confidence that a change point occurred at segment <NUM> where the peak <NUM> was.

<FIG> illustrates the hardness profile <NUM> of <FIG> with a first change point <NUM> and a second change point <NUM> marked as identified by the iterative cumulative sum process discussed in <FIG> and <FIG>. The process used to find the first change point <NUM> was repeated on a subset of the samples. The subsets were bordered by at least one of the change points.

<FIG> illustrates a cumulative difference <NUM> for segments <NUM>-<NUM> of the hardness profile of <FIG> plotted with random noise <NUM>. The random noise <NUM> was produced from the values of the same subset. The peak <NUM> of the cumulative difference <NUM> indicated that there was a potential change point at that point in the blasthole. The random noise <NUM> was used to provide a confidence level that the peak <NUM> represented a change point.

<FIG> is a graph <NUM> of a distribution of the difference between the maximum and minimum values of the cumulative difference of the random permutations. In the illustrated example, the difference between the maximum and the minimum values for the original data was <NUM>. As illustrated in <FIG>, <NUM>% of the random permutations exceeds the <NUM> value. Therefore, there was a <NUM>% confidence that a change point occurred at segment <NUM> where the peak <NUM> was. In this example, the threshold was set to <NUM>% confidence to reduce the false detection of change points. Therefore, segment <NUM> was not identified as a change point.

<FIG> illustrates the hardness profile <NUM> of <FIG> with a first change point <NUM>, a second change point <NUM>, and a non-change point <NUM> marked as identified by the iterative cumulative sum process discussed with reference to <FIG>, <FIG>, and <FIG>.

The process used to find the change points was repeated on a subset of the samples, with the subset bordered by either change points, data boundaries (i.e., data point <NUM> or data point <NUM>), or combinations thereof. The process was repeated on increasingly narrow subsets of samples, until a peak was identified for a particular subset that was not determined to be a change point. For example, after the non-change point <NUM> was identified, data points <NUM>-<NUM> (i.e., hole depth from <NUM> feet to <NUM> feet) were not further evaluated for additional peaks or change points. <FIG> illustrates the hardness profile <NUM> of <FIG> after multiple subsets were analyzed for change points. Change points were found at segments <NUM>, <NUM>, and <NUM> with confidence levels of <NUM>%, <NUM>%, and <NUM>%, respectively. Additional peaks were found that were determined to be non-change points at segments <NUM>, <NUM>, <NUM>, and <NUM> with confidence levels of <NUM>%, <NUM>%, <NUM>%, and <NUM>%, respectively, Thus, prior to application of a stemming depth, four groups were identified. A representative hardness value for each of the groups would next be determined and a target emulsion density assigned.

<FIG> illustrates another example hardness profile. The mean hardness value and standard deviation of that mean are depicted numerically and on the graph. Change points were identified for the hardness profile using the same process as applied to example hardness profile <NUM>. The hardness data was segmented on a per-foot basis. A stemming depth of <NUM> feet was applied to the hardness profile. Three change points remained after application of the stemming depth. The change points were at about <NUM> feet, <NUM> feet, and <NUM> feet and defined four distinct groups. A representative hardness value would next be determined for each of the groups and a target emulsion density assigned.

<FIG> illustrates a block diagram of an explosive delivery system <NUM> for automatically varying the density of an emulsion matrix in a blasthole. As shown, the explosive delivery system <NUM> may include a processor <NUM>, memory <NUM>, data interface <NUM>, and computer-readable storage medium <NUM>. A bus <NUM> may interconnect various integrated and/or discrete components.

The processor <NUM> may include one or more general-purpose devices, such as an Intel®, or other standard microprocessor. The processor <NUM> may include a special-purpose processing device, such as ASIC, SoC, SiP, FPGA, PAL, PLA, FPLA, PLD, or other customized or programmable device. The processor <NUM> may perform distributed (e.g., parallel) processing to execute or otherwise implement functionalities of the presently disclosed embodiments.

The computer-readable storage medium <NUM> may include static RAM, dynamic RAM, flash memory, one or more flip-flops, ROM, CD-ROM, DVD, disk, tape, or magnetic, optical, or other computer storage medium. The computer-readable storage medium <NUM> may include geologic data <NUM>, and one or more programs to analyze the data.

For example, the computer-readable storage medium <NUM> may comprise a blasthole profiler <NUM>, an emulsion density lookup table <NUM>, and a confidence indexer <NUM>. The blasthole profiler <NUM> may receive dimensions of the blasthole and determine any change points within a geologic profile, wherein the geologic profile comprises hardness values representing hardness characteristics along a length of the blasthole. The blasthole profiler <NUM> may also segment the blasthole into one or more groups separated by any identified change points. The confidence indexer <NUM> may evaluate the strength of each change point. The emulsion density lookup table <NUM> may be used to determine the target emulsion density within each group. A controller <NUM> may prepare a signal to be sent to a mixer to cause the emulsion explosive to be a target density associated with a group of the blasthole being filled.

Table <NUM> list an example of the information that could be included in the emulsion density lookup table <NUM>. Table <NUM>, for example, could be used with the groups (i.e., segments) identified in <FIG> and <FIG> to determine the target emulsion density for each of the groups. For example, when an algorithm is used to calculate hardness values from drilling data, then the algorithm may also be used to approximate the target emulsion density for particular hardness values as part of generating Table <NUM>. Likewise, variations of Table <NUM> utilizing geologic values in addition to or instead of hardness values could also be used. The approximations determined by the algorithm could then be confirmed or refined based on experience with actual test blasts in the material to be blasted.

In some embodiments, the look up table can be tailored based on additional factors. For example, the variables of the lookup table may be varied based on the nature of the material in the ground (e.g., granite, sandstone, shale), the location of the mine, and current conditions. In some embodiments, the explosive delivery system may not find change points and instead use the average value of each blast hole and the look up table to identify an explosive density for each hole.

<FIG> illustrates a top view of a blast pattern <NUM> showing the average hardness of each hole according to one embodiment. An energy profile may be based on segmented and grouped blastholes. In the illustrated embodiment, the blast pattern has been segmented into five groups (e.g., 1402a-1402e). Each group represents one or more blastholes with similar hardness characteristics bordered by change points. The distance of the blast pattern <NUM> where change points in the hardness values may be determined may be along each row or a line of holes in a burden direction. In some embodiments, change points may be determined in both spacing and burden directions of a blast pattern. In some embodiments, change points may be determined row by row. In some embodiments, an anchor blasthole may be used as a starting location, and change points are determined across a line in the blast plan at a plurality of angles.

<FIG> illustrates a method of segmenting and grouping blastholes based on change points in geologic values, such as hardness values. <FIG> illustrates a flow chart of one embodiment of a method <NUM> of delivering explosives. The method <NUM> described with reference to <FIG> may be executed by processor circuitry, such as the processor circuitry <NUM> of <FIG>.

In this embodiment, the method <NUM> comprises receiving <NUM> a geologic profile and a blast pattern. The geologic profile may include geologic values representing one or more geologic characteristics of the plurality of blastholes in the blast plan. In some embodiments, the method includes receiving drilling data comprising geologic hardness characteristics, a diameter of the blasthole, and a length of the blasthole. This information may be provided directly by data received during a drilling operation, or may be operator entered. In some embodiments, the method includes receiving seismic data. In some embodiments, the method <NUM> includes generating a hardness profile based on drilling data and/or seismic data.

The method <NUM> further includes determining <NUM> any change points also sometimes referred to as inflection points within the geologic profile across the coordinates of the plurality of blastholes in the blast plan. See <FIG> for an illustration of how one embodiment finds change points within the geologic profile. In some geologic profiles there are no change points. This results in a single target emulsion density to be used for an entire blast plan. For clarification, even if there are no change points in hardness horizontally in the plan, the operator may still use multiple densities within each hole for the same reasons they may use multiple segments in any other blast. In other geologic profiles there are one or more change points, such as multiple change points resulting in multiple groups with one or more different target emulsion densities. For example, the change points may be determined using a sequential analysis technique, such as a cumulative sum technique, or other techniques that determine the confidence level of a change in momentum in a data series.

The method <NUM> further includes segmenting <NUM> the plurality of blastholes into one or more groups separated by any identified change points across the coordinates of the plurality of blastholes. The method <NUM> further includes determining <NUM> a representative geologic value for each group. The representative geologic value may be defined by a probability distribution, an average geologic value, a maximum geologic value, or a minimum geologic value for a particular group. Examples of a probability distribution include the mean, median, or mode of the geologic values for a particular group.

The method <NUM> further includes determining <NUM> a target explosive energy value, such as a target emulsion density, for each group based on the representative geologic value for each group, thereby generating a target explosive energy profile comprising target explosive energy values for each blasthole in the plurality of blastholes. In some embodiments, determining the target explosive energy value for each group comprises accessing a table and locating the target explosive energy value based on the representative geologic value associated with each group. The table can include target explosive energy values for a plurality of geologic values.

The method <NUM> may further include controlling <NUM> a flow rate of the energy-modulating agent to the mixer to achieve the target explosive energy value for the group associated with a blasthole being filled. For example, the method <NUM> may determine the blasthole based on GPS location, or in relation to a previous blasthole, and adjust the explosive to the target explosive energy value associated with the group of which the blasthole is a part, such as by adjusting the density of the explosive when the explosive contains an emulsion explosive.

<FIG> illustrates a block diagram of an explosive delivery system <NUM> for automatically varying the density of an emulsion matrix in between blastholes in a blast pattern. As shown, the explosive delivery system <NUM> may include a processor <NUM>, memory <NUM>, data interface <NUM>, and computer-readable storage medium <NUM>. A bus <NUM> may interconnect various integrated and/or discrete components.

For example, the computer-readable storage medium <NUM> may comprise a blast plan profiler <NUM>, an emulsion density lookup table <NUM>, and a confidence indexer <NUM>. The blast plan profiler <NUM> may receive dimensions of the blast plan and location of blastholes and determine any change points within a geologic profile of the blast plan. In some embodiments, the geologic profile comprises an average geologic value for each blasthole. The blast plan profiler <NUM> may also segment the blastholes of the blast plan into one or more groups separated by any identified change points. The confidence indexer <NUM> may evaluate the strength of each change point. The emulsion density lookup table <NUM> may be used to determine the target emulsion density within each group. A controller <NUM> may prepare a signal to be sent to a mixer to cause the emulsion explosive to be a target density associated with the blasthole being filled.

Claim 1:
A method (<NUM>, <NUM>) of delivering explosives comprising:
receiving a geologic profile;
determining, via processor circuitry (<NUM>), any inflection points in geologic values within the geologic profile, wherein the geologic values represent geologic characteristics along a length of a blasthole (<NUM>) or along a distance of a blast pattern;
segmenting, via processor circuitry, the geologic profile into groups (<NUM>, <NUM>) separated by any identified inflection points;
determining, via processor circuitry, a target explosive energy value for each group based on a representative geologic value for each group, thereby generating a target explosive energy profile comprising the target explosive energy value for each group, wherein the representative geologic value is defined by a probability distribution, an average geologic value, a maximum geologic value, or a minimum geologic value for a particular group;
delivering via a delivery system (<NUM>) an explosive (<NUM>) with explosive energy values according to the target explosive energy profile;
wherein an energetic substance and an energy-modulating agent are mixed to form the explosive.