CA3140790A1 - System, method, and medium for predicting and mitigating hydrogen sulphide generated in bitumen processing - Google Patents

Abstract

There are provided systems, methods, and processor-readable media for predicting and mitigating hydrogen sulphide (H2S) generated during bitumen processing. A bitumen ore processing system is configured to process bitumen-comprising material, derived from bitumen ore, via a process configuration. A trained prediction machine learning model is used to process process parameter information to predict a H2S concentration measure. A H2S mitigation module is then used to process the process parameter information and the H25 concentration measure predicted by the trained prediction machine learning model such that recommended operating parameter information is obtained. The recommended operating parameter information is effective for establishing a modified process configuration for which the H25 concentration measure is mitigated.

Description

SYSTEM, METHOD, AND MEDIUM FOR PREDICTING AND MITIGATING
HYDROGEN SULPHIDE GENERATED IN BITUMEN PROCESSING
FIELD
[0001] The present disclosure relates to optimizing mineral processing, and in particular to systems, methods, and processor-readable media for predicting and mitigating hydrogen sulphide generated in bitumen processing.
BACKGROUND

[0002] Processing of bitumen ore to generate a bitumen product typically results in the generation of hydrogen sulphide (H2S, also referred to herein as H2S
or hydrogen sulfide) due to the presence of H2S or an H2S precursor such as metal sulphides, in the bitumen ore. H2S presents dangers to both equipment and personnel involved in the processing of bitumen-comprising material: equipment can be corroded by the acidic (low pH) conditions created by H2S, and H2S in gaseous or liquid form presents a safety hazard to personnel.

[0003] Accordingly, it would be useful to provide techniques for predicting and/or mitigating harmful levels of H2S generated during bitumen processing.
SUMMARY

[0004] In one aspect, there is provided a method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is Date recue / Date received 2021-11-30 processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;
wherein:
the process parameter information includes at least one process parameter value;
each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
processing the process parameter information, using a trained prediction machine learning model, to predict a hydrogen sulphide concentration measure of a processed material, defined by one of the one or more derivative materials, wherein the hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material;
Date recue / Date received 2021-11-30 and based on the hydrogen sulphide concentration measure, modifying the original process configuration, such that a modified process configuration is established;
wherein:
the a concentration of hydrogen sulphide of the processed material, established by the processing of the bitumen-comprising material by the modified process configuration, is less than the concentration of hydrogen sulphide of the processed material established by the processing of the bitumen-comprising material by the original process configuration,

[0005] In another aspect, there is provided a method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;
wherein:
Date recue / Date received 2021-11-30 the process parameter information includes at least one process parameter value;
each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
processing the process parameter information, using a trained prediction machine learning model, to predict a hydrogen sulphide concentration measure of a processed material, defined by one of the one or more derivative materials, wherein the hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material;
and based on the hydrogen sulphide concentration measure, modifying the original process configuration with effect that the concentration of hydrogen sulphide of the processed material is reduced, such that a modified processed material is established.

[0006] In another aspect, there is provided a method for training a prediction machine learning model, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material Date recue / Date received 2021-11-30 outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;
wherein:
the process parameter information includes at least one process parameter value;
each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
obtaining a hydrogen sulphide concentration measure, wherein the obtained hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material;
providing the process parameter information as an input to the prediction machine learning model, thereby generating a predicted hydrogen sulphide concentration measure as the output of the prediction machine learning model;
processing the predicted hydrogen sulphide concentration measure and the obtained hydrogen sulphide concentration measure to generate a loss;
and adjusting a plurality of learnable parameters of the prediction machine learning model based on the loss.
Date recue / Date received 2021-11-30

[0007] In another aspect, there is provided a method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;
wherein:
the process parameter information includes at least one process parameter value;
each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
and processing the process parameter information, using a trained prediction machine learning model, to predict a hydrogen sulphide concentration measure of a processed material, defined by one of the one or more derivative materials, wherein Date recue / Date received 2021-11-30 the hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material.

[0008] In another aspect, there is provided a method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth inernnediate is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least fractionatable bitumen-rich separation fraction and a solids-rich separation fraction; and fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility;
Date recue / Date received 2021-11-30 wherein:
the liquid recovered bitumen-rich fraction includes:
at least 99 weight % bitumen, based on the total weight of the liquid recovered bitumen-rich fraction; and nnercaptan material defined by at least one nnercaptan compound, each one of the at least one nnercaptan compound, independently, is of formula (I):
R-S-H
wherein R is an organic group;
and the liquid recovered bitumen-rich fraction is disposed at a temperature of less than 130 degrees Celsius.

[0009] In another aspect, there is provided a method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth inernnediate is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-Date recue / Date received 2021-11-30 aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least fractionatable bitumen-rich separation fraction and a solids-rich separation fraction;
fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility; and conducting a bitumen-rich product material, derived from the liquid recovered bitumen-rich fraction, to a storage tank, such that the bitumen-rich product material becomes emplaced within the storage tank, such that stored bitumen-rich product material is established within the storage tank;
wherein:
the liquid recovered bitumen-rich fraction includes:
at least 99 weight % bitumen, based on the total weight of the Date recue / Date received 2021-11-30

- 10 -liquid recovered bitumen-rich fraction; and nnercaptan material defined by at least one nnercaptan compound, each one of the at least one nnercaptan compound, independently, is of formula (I):
R-S-H
wherein R is an organic group;
wherein:
the content of the nnercaptan material within the liquid recovered bitumen-rich fraction is a H2S-generation effective nnercaptan content; and an equivalent nnercaptan content, to the H2S-generation effective nnercaptan content, within the stored bitumen product material, is effective, at a temperature of at least 130 degrees Celsius, for effecting establishment of an H2S concentration of greater than 2 ppm within the stored bitumen output material;
and the liquid recovered bitumen-rich fraction is disposed at a temperature of less than 130 degrees Celsius [0010] In another aspect, there is provided a method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
Date recue / Date received 2021-11-30

- 11 -admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth inernnediate is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least fractionatable bitumen-rich separation fraction and a solids-rich separation fraction;
fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative Date recue / Date received 2021-11-30

- 12 -volatility;
modulating a temperature representative of the temperature of the liquid recovered bitumen-rich fraction, based upon the concentration of H2S within the liquid recovered bitumen-rich fraction.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] Reference will now be made, by way of example, to the accompanying drawings which show example implementations of the present application, and in which:
[0012] FIG. 1A is a block diagram showing the operations of a bitumen ore processing system suitable for implementation of examples described herein.

[0013] FIG. 1B is a block diagram showing detailed operations of a solvent recovery unit of the bitumen ore processing system of FIG. 1A.

[0014] FIG. 2 is a block diagram of an example computing system suitable for implementation of examples described herein.

[0015] FIG. 3A is a block diagram of an example process control module operating in a training mode, in accordance with example implementations described herein.

[0016] FIG. 3B is a block diagram of an example process control module operating in a deployment mode, in accordance with example implementations described herein.

[0017] FIG. 4 is a flowchart showing operations of a method for processing bitumen-comprising material derived from a bitumen ore, in accordance with example implementations described herein.
Date recue / Date received 2021-11-30

[0018] Similar reference numerals can have been used in different figures to denote similar components.
DESCRIPTION OF EXAMPLE IMPLEMENTATIONS

[0019] As used herein, statements that a second item (e.g., a signal, value, scalar, vector, matrix, calculation, or bit sequence) is "based on" a first item can mean that characteristics of the second item are affected or determined at least in part by characteristics of the first item. The first item can be considered an input to an operation or calculation, or a series of operations or calculations, that produces the second item as an output that is not independent from the first item.

[0020] The present disclosure describes systems, methods, and processor-readable media for predicting and mitigating hydrogen sulphide (H25, also referred to herein as H25 or hydrogen sulfide) generated during bitumen processing.

[0021] In some embodiments, the techniques described herein can be used to predict and/or mitigate H25 in a "sweet" bitumen secondary production facility.
Some bitumen-processing equipment is built to specifically resist corrosion due to the presence of H25. "Sour" bitumen production facilities, designed to process bitumen-comprising material known to contain high levels of sulphides, often use such equipment as part of a napthenic solvent-based process to generate a bitumen product. However, "sweet" bitumen production facilities typically use a paraffinic solvent-based process to process bitumen-containing material expected to contain low levels of sulphides, and do not typically use equipment designed to resist the corrosive effects of H25. When a sweet bitumen production facility encounters bitumen ore containing an unexpectedly large concentration of sulphides, or bitumen-comprising material derived therefrom, a high concentration of H25 can be generated at one or more stages within the facility, thereby damaging the Date recue / Date received 2021-11-30 equipment. Such an event is referred to herein as an "H25 event" or an "H25 spike". Furthermore, both sweet and sour bitumen production facilities encountering an H25 event can experience safety hazards to personnel and/or lowered product quality due to the presence of H25 in the bitumen-rich product material of the facility. Storage of bitumen-rich product material (e.g., in storage tanks 3011) can be complicated by high levels of H25 in the material, again due to potential hazards to equipment and personnel. In some embodiments, for example, it is desirable to maintain the concentration of H25 within the bitumen-rich product material below 2 ppm.

[0022] Few options are currently available to mitigate the dangers of H25 generated in bitumen production. In some cases, it is possible to introduce a chemical additive to one or more stages within the bitumen production process such that the acidity of a liquid material within the facility is reduced; for example, amine material can be injected or added to a gas or liquid material within the facility to reduce its acidity and thereby reduce the amount of H25 evolved during the bitumen production process. However, such amine-based mitigation measures must necessarily be either applied continuously (i.e., a constant amount of amine added over time) or applied after the fact in response to detecting an H25 event that has already occurred. For example, a liquid output of the facility can be measured for acidity and/or iron content (indicative of corrosion of iron-containing equipment), thereby introducing a significant delay before mitigating steps can be taken, particularly if the measurements are only made intermittently (e.g. a few times per day). In a context in which H25 events are relatively infrequent and/or severe, these approaches to mitigation can result in ineffective and/or inefficient mitigation of H25 events, as either a large amount of amine material would need to be added constantly, or H25 events could only be mitigated after a long delay in Date recue / Date received 2021-11-30 which H2S-related risks and damage to equipment and personnel have already occurred.

[0023] Accordingly, the use of machine learning to proactively predict H2S
events can allow for H2S events to be mitigated prospectively, before H2S
concentration can rise to dangerous or damaging levels, by taking mitigating steps of a severity proportional to the expected severity of the H2S event. Thus, examples described herein can provide more effective and/or more efficient mitigation of H2S events in bitumen processing than currently available techniques.
Described examples can thereby result in lower operating costs, lower maintenance costs, lower risks of equipment failure, increased personnel safety, and/or higher product quality.

[0024] FIG. 1A shows a bitumen ore processing system 10 for processing bitumen-comprising materials derived from bitumen ore 12. The bitumen ore processing system 10 is suitable for performing one or more methods described herein. A method is provided for processing a bitumen-comprising material, and the method includes supplying one or more material inputs to a process configuration, wherein a one of the one or more material inputs is a bitumen-comprising material input. Other ones of the material inputs include, for example, water, air, solvent material, or other chemical additives, as further explained below.
The supplying of the one or more material inputs to the process configuration is with effect the bitumen-comprising material is processed via the process configuration. The processing is with effect that one or more derivative materials, derived from the one or more material inputs, are established. The one or more derivative materials include at least one or more product material outputs.
Each one of the one or more product material outputs, independently, is discharged from the process configuration. At least one, of the one or more product material Date recue / Date received 2021-11-30 outputs, includes bitumen. In some embodiments, for example, the one or more derivative materials include at least one intermediate material.

[0025] A process configuration defines one or more processes, conducted under defined process conditions, via which the bitumen-comprising material is converted to the one or more derivative materials. Each one of the one or more processes, independently, is effectuated via a respective one or more unit operations. The unit operations are co-operatively configured for effectuating production of the at least one product material, such that the one or more derivative materials includes the at least one final product material. Each one of the one or more unit operations, independently, includes one or more of mixing, separation, and chemical reaction. Additionally, each one of the one or more unit operations, independently, can include energy transfer, such as heating and/or cooling. Each one of the unit operations, independently, includes one or more material inputs and one or more material outputs. In some embodiments, for example, the one or more derivative materials includes an intermediate material, derived from the bitumen-comprising material, and from which is derived at least one of the at least one product material. In some embodiments, for example, the intermediate material is a material output that is discharged from a first unit operation and supplied to a second unit operation as a material input. In some embodiments, for example, the intermediate material is a material being processed by a unit operation, which is derived from a material input that is supplied to the unit operation, and from which is derived a material output that is discharged from the unit operation.

[0026] In some embodiments, for example, the bitumen-comprising material is a bitumen ore 12. In some embodiments, for example, the bitumen ore 12 includes solid particulate material, and, in such embodiments, for example, the solid particulate material includes at least one of sand and clay. In some Date recue / Date received 2021-11-30 embodiments, for example, the bitumen ore includes from eight (8) weight %
bitumen, based on the total weight of the bitumen ore, to 12 weight % bitumen, based on the total weight of the bitumen ore. In some embodiments, for example, the bitumen ore includes oil sands.

[0027] In some embodiments, for example, the bitumen-comprising material is derived from a surge pile. In some embodiments, for example, the bitumen-comprising material is obtained from a surge pile. In some embodiments, for example, the bitumen-comprising material of the surge pile is defined by a size-reduced bitumen ore 20 (i.e. bitumen ore which has been subjected to a size reduction operation (e.g. crushing)) within an ore preparation plant.

[0028] In some embodiments, for example, the processing includes admixing a bituminous material 16, derived from the bitumen ore, with water 17 and air 18, such that a multi-phase bituminous admixture 14 is produced. In some embodiments, for example, the admixing is effected within a slurry preparation plant (of the ore preparation plant), and continues within the hydrotransport system, while being conducted to the froth flotation unit operation (see below). In some embodiments, for example, the admixing includes admixing with a conditioning agent 22, for mitigating interference of clay particles to adherence of the bitumen to air bubbles during froth flotation (see below). In some embodiments, for example, the conditioning agent includes sodium hydroxide.

[0029] In some embodiments, for example, a multi-phase bituminous feed material 102, that is derived from the multi-phase bituminous admixture 14, is separated into at least a bitumen-rich froth overflow 104 and a bitumen-lean underflow via froth flotation 106. In some embodiments, for example, the multi-phase bituminous feed material 102 is the multi-phase bituminous admixture 14.
In some embodiments, for example, the separation is effected within a froth flotation unit operation of a primary bitumen production facility 100.
Date recue / Date received 2021-11-30

[0030] In some embodiments, for example, the multi-phase bituminous feed material 102 includes from eight (8) weight % bitumen, based on the total weight of the multi-phase bituminous feed material 102, to 14 weight % bitumen, based on the total weight of the multi-phase bituminous feed material 102. In some embodiments, for example, the multi-phase bituminous feed material 102 also includes 50 weight % solid particulate material, based on the total weight of the multi-phase bituminous feed material 102, to 55 weight % solid particulate material, based on the total weight of the multi-phase bituminous feed material 102. In some embodiments, for example, the multi-phase bituminous feed material 102 includes 25 weight % water, based on the total weight of the multi-phase bituminous feed material 102, to 40 weight % water, based on the total weight of the multi-phase bituminous feed material 102. In some embodiments, for example, the density of the multi-phase bituminous feed material 102 is about 1.40 tonnes per cubic metre.

[0031] In some embodiments, for example, the separation, via froth flotation, is effected at a temperature of at least 35 degrees Celsius. In some embodiments, for example, the separation, via froth flotation, is effected at a temperature that is from 35 degrees Celsius to 70 degrees Celsius. In some embodiments, for example, the separation, via froth flotation, is effected at a temperature that is from degrees Celsius to 60 degrees Celsius at approximately atmospheric pressure.

[0032] In some embodiments, for example, the separation, via froth flotation, is with effect that bitumen concentrates within the bitumen-rich froth overflow 104, such that the bitumen-rich froth overflow 104 includes at least 50 weight %
bitumen, based on the total weight of the bitumen-rich froth overflow 104, such as, .. for example, from 50 weight % bitumen, based on the total weight of the bitumen-rich froth overflow 104, to 60 weight % bitumen, based on the total weight of the bitumen-rich froth overflow 104. In some embodiments, for example, the bitumen-Date recue / Date received 2021-11-30 rich froth overflow 104 includes from eight (8) weight % solid particulate material, based on the total weight of the bitumen-rich froth overflow 104, to 15 weight %
solid particulate material, based on the total weight of the bitumen-rich froth overflow 104. In some embodiments, for example, the bitumen-rich froth overflow 104 includes from ten (10) weight % solid particulate material, based on the total weight of the bitumen-rich froth overflow 104, to 13 weight % solid particulate material, based on the total weight of the bitumen-rich froth overflow 104. In some embodiments, for example, the total content of fine solid particulate material (also called "fines", i.e. solid particulate material of less than 45 microns in width) within the solid particulate material is at least 10-20% total solids in the froth stream, consisting of about 40 to 60 weight % fines. In some embodiments, for example, the water content of the bitumen-rich froth overflow 104 is from 30 weight %
water, based on the total weight of the bitumen-rich froth overflow 104, to 40 weight % water, based on the total weight of the bitumen-rich froth overflow 104.

[0033] In some embodiments, for example, the separation, via froth flotation, is with further effect that the bitumen-lean underflow 106 includes less than one (1) weight % bitumen, based on the total weight of the bitumen-lean underflow 106. In some embodiments, for example, the density of the bitumen-lean underflow 106 is less than 1.6 tonnes per cubic metre. In some embodiments, for example, the bitumen-lean underflow 106 includes at least 50 weight % solids, based on the total weight of the bitumen-lean underflow 106.

[0034] In some embodiments, for example, the separating of the multi-phase bituminous feed material additionally produces a middlings product 108 having a middlings density that is intermediate of the overflow density and the underflow density. In some embodiments, for example, the middlings product 108 includes from one (1) weight % bitumen, based on the total weight of the middlings product 108, to four (4) weight % bitumen, based on the total weight of the middlings Date recue / Date received 2021-11-30 product 108. In some embodiments, for example, the density of the middlings product 108 is from 1.05 tonnes per cubic metre to 1.20 tonnes per cubic metre. A
middlings product feed 110, derived from the middlings product 108, is separated, via froth flotation, into at least a lower quality bitumen-enriched froth overflow 112 and a bitumen-depleted underflow 114, and the lower quality bitumen-enriched froth overflow 112 is recycled such that a portion of the multi-phase bituminous feed material 102 derives from the lower quality bitumen-enriched froth overflow 112. The bitumen-lean underflow 106 and bitumen-depleted underflow 114 are conducted to a tailings plant for treatment and disposal. In this respect, in some embodiments, for example, each one of the bitumen-lean underflow 106 and bitumen-depleted underflow 114, independently, defines a one of the one or more product material outputs.

[0035] In those embodiments the separating of the multi-phase bituminous feed material additionally produces a middlings product 108, the primary bitumen production facility 100 includes a primary froth flotation circuit 120 and a second froth flotation circuit 130, and the separating of the multi-phase bituminous feed material 102 is effected within the primary froth flotation circuit 120 and the fractionation of the middlings product feed 110 is effected within the secondary froth flotation circuit 130. Each one of the primary froth flotation circuit 120 and the second froth flotation circuit 130, independently, includes one or more flotation cells to facilitate the respective separation via froth flotation.

[0036] In some embodiments, for example, the a bitumen-rich froth overflow feed 105, derived from the bitumen-rich froth overflow 104, is de-aerated, with effect that a de-aerated bitumen-rich intermediate 221 is produced. In some embodiments, for example, the de-aeration is effected within a froth deaerator 220.
In some embodiments, for example, the bitumen-rich froth overflow feed is the bitumen-rich froth overflow 104. In some embodiments, for example, the bitumen-Date recue / Date received 2021-11-30 rich froth overflow 104 includes at least 40 volume % air bubbles, based on the total volume of the bitumen-rich froth overflow 104. In some embodiments, for example, the de-aeration process also generates a gaseous output material (not shown in FIG. 1A).

[0037] FIG. 1B shows further details of the operations of the secondary bitumen production facility 200 shown in FIG. 1A. The processing of the de-aerated bitumen-rich intermediate 221 can be performed using the components of the secondary bitumen production facility 200 shown in FIG. 1B in some embodiments.

[0038] In some embodiments, for example, a de-aerated bitumen-rich intermediate feed 202, derived from the de-aerated bitumen-rich intermediate 221, is admixed with solvent material 204, with effect that a conditioned bitumen-rich intermediate 231 is obtained. In some embodiments, for example, the de-aerated bitumen-rich intermediate feed 202 is the de-aerated bitumen-rich intermediate 221. In some embodiments, for example, the de-aerated bitumen-rich intermediate feed 202 is admixed with the solvent material in a weight ratio from 0.4 to 0.7. In some embodiments, for example, the solvent material is light hydrocarbon material.

[0039] In this respect, in some embodiments, for example, the de-aerated bitumen-rich intermediate feed 202 includes at least 50 weight % bitumen, based on the total weight of the de-aerated bitumen-rich intermediate feed 202, such as, for example, from 50 weight % bitumen, based on the total weight of the de-aerated bitumen-rich intermediate feed 202, to 60 weight % bitumen, based on the total weight of the de-aerated bitumen-rich intermediate feed 202. In some embodiments, for example, the de-aerated bitumen-rich intermediate feed 202 includes from eight (8) weight % solid particulate material, based on the total weight of the de-aerated bitumen-rich intermediate feed 202, to 15 weight %
solid particulate material, based on the total weight of the de-aerated bitumen-rich Date recue / Date received 2021-11-30 intermediate feed 202. In some embodiments, for example, the de-aerated bitumen-rich intermediate feed 202 includes from ten (10) weight % solid particulate material, based on the total weight of the de-aerated bitumen-rich intermediate feed 202, to 13 weight % solid particulate material, based on the total weight of the de-aerated bitumen-rich intermediate feed 202. In some embodiments, for example, the total content of fine solid particulate material (i.e.
fines) within the solid particulate material is at least 10-20% total solids in the froth stream, consisting of about 40 to 60 weight % fines. In some embodiments, for example, the water content of the de-aerated bitumen-rich intermediate feed 202 is from 30 weight % water, based on the total weight of the de-aerated bitumen-rich intermediate feed 202, to 40 weight % water, based on the total weight of the de-aerated bitumen-rich intermediate feed 202.

[0040] In some embodiments, for example, the light hydrocarbon material is a paraffinic material, and the paraffinic material includes alkane-consisting material, wherein the alkane-consisting material includes at least one alkane. In some embodiments, for example, each one of the at least one alkane, independently, has a total number of carbon atoms, and the total number of carbon atoms is from four (4) to 20. Suitable alkanes include butane, pentane, hexane, and heptane.

[0041] In some embodiments, for example, the light hydrocarbon material is .. a naphthenic material, and the naphthenic material includes cycloalkane-consisting material, wherein the cycloalkane-consisting material includes at least one cycloalkane. In some embodiments, for example, each one of the at least one cycloalkane, independently, has a total number of carbon atoms, and the total number of carbon atoms is from four (4) to 20.

[0042] In some embodiments, for example, the admixing of the de-aerated bitumen-rich intermediate feed 202 with the solvent material 204 is with effect that the bitumen, of the de-aerated bitumen-rich intermediate feed 202, becomes Date recue / Date received 2021-11-30 sufficiently associated with the solvent material 204 such that a conditioned bitumen-rich intermediate 231 is produced, and a conditioned bitumen-rich intermediate feed 232, derived from the conditioned bitumen-rich intermediate 231, becomes separable into at least a bitumen-rich separation fraction 208 and a solids-rich separation fraction 210 via gravity separation. In this respect, the process includes, after the production of the conditioned bitumen-rich intermediate 231, separation of the conditioned bitumen-rich intermediate feed 232 into at least the bitumen-rich separation fraction 208 and the solids-rich separation fraction 210 via gravity separation. In some embodiments, for example, the bitumen-rich separation fraction 208 defines a one of the one or more product material outputs.
In some embodiments, for example, the conditioned bitumen-rich intermediate feed 232 is the conditioned bitumen-rich intermediate 231.

[0043] In some embodiments, for example, both of: (i) the admixing of de-aerated bitumen-rich intermediate feed 202 with the solvent material 204, and (ii) the separation of the conditioned bitumen-rich intermediate feed 232 into at least the bitumen-rich separation fraction 208 and the solids-rich separation fraction 210 via gravity separation, is effected within the same unit operation, such as, for example, a froth treatment unit 230.

[0044] In some embodiments, for example, recovery of a recovered bitumen-rich fraction 302, from the bitumen-rich separation fraction 208, is effected via processing via a solvent recovery unit 300, by fractionation of the bitumen-rich separation fraction 208 into at least a recovered bitumen-rich fraction 302 and a recovered solvent-rich fraction 3068. Referring to Figure 1B, in some embodiments, for example, the recovery of the recovered bitumen-rich fraction 302 is effected in a three stage fractionation. In this respect, in some embodiments, for example, for effecting the three stage fractionation, the solvent recovery unit 300 includes a flash drum 3001, a distillation column 3002, and a flash drum 3003.
Date recue / Date received 2021-11-30

[0045] In this respect, in some embodiments, for example, a bitumen-rich fractionatable material 304, derived from the bitumen-rich separation fraction 208, is fractionated, via flash vaporization, into a liquid first intermediate bitumen-enriched fraction 3021 and a gaseous first solvent-rich fraction 3061. In some embodiments, for example, the fractionatable bitumen-rich separation fraction is the bitumen-rich separation fraction 208. The flash evaporation is effected within a fractionation zone 3001A defined within the flash drum 3001. In some embodiments, for example, the fractionation zone 3001A is disposed at a temperature of from 115 degrees Celsius to 130 degrees Celsius, and at a pressure of from 450 kPa (g) to 550 kPa (g). In some embodiments, for example, prior to being supplied to the flash drum 3001, the fractionatable bitumen-rich separation fraction 304 is pre-heated within a pre-heater 3004.

[0046] In some embodiments, for example, a first intermediate enriched bitumen fractionatable material 3022, derived from the liquid first intermediate bitumen-enriched fraction 3021, is then fractionated, via distillation, into at least a liquid second intermediate bitumen-enriched fraction 3023 and a gaseous second solvent-rich fraction 3062. In some embodiments, for example, the first intermediate enriched bitumen fractionatable material 3022 is the liquid first intermediate bitumen-rich fraction 3021. The distillation is effected within a fractionation zone 3002A of the distillation column 3002. In some embodiments, for example, the fractionation zone 3002A is disposed at a temperature of from 160 degrees Celsius to 215 degrees Celsius and at a pressure of from 100 kPa (g) to 130 kPa (g). In some embodiments, for example, prior to being supplied to the distillation column 3002, first intermediate enriched bitumen fractionatable material 3022 is pre-heated within a pre-heater 3005. In some embodiments, for example, steam is supplied to the distillation column 3002 for enhancing the fractionation.
Date recue / Date received 2021-11-30

[0047] In some embodiments, for example, a second intermediate enriched bitumen fractionatable material 3024, derived from the liquid second intermediate bitumen-enriched fraction 3023, is then fractionated, via flash vaporization, into at least a liquid recovered bitumen-rich fraction 302 and a gaseous third solvent-rich fraction 3063. In some embodiments, for example, the second intermediate enriched bitumen fractionatable material 3024 is the liquid second intermediate bitumen-rich fraction 3023. The flash evaporation is effected within a fractionation zone 3003A of the flash drum 3003. In some embodiments, for example, the fractionation zone 3003A is disposed at a temperature of at least 125 degrees Celsius and below 130 degrees Celsius and at a pressure of from minus 75 kPa (g) to 0 kpa (g) (i.e. atmospheric pressure). In some embodiments, for example, prior to being supplied to the flash drum 3003, the second intermediate enriched bitumen fractionatable material 3024 is cooled within a cooler 3006.

[0048] In some embodiments, for example, a bitumen product material is derived from the liquid recovered bitumen-rich fraction 302. In some embodiments, for example, the bitumen product material is the recovered bitumen-rich fraction 302. In some embodiments, for example, the bitumen product material is stored in storage tanks 3011 prior to being transported to market. In some embodiments, for example, the liquid recovered bitumen-rich fraction 302 includes at least 99 weight % bitumen, based on the total weight of the bitumen product material. In this respect, in some embodiments, for example, the bitumen product material defines a one of the one or more product material outputs.

[0049] In some embodiments, for example, the gaseous first solvent-rich fraction 3061, or a derivative thereof, is cooled via cooler 3007, with effect that a mixed fluid first solvent-rich intermediate precursor 3064 is obtained, the gaseous second solvent-rich fraction 3063, or a derivative thereof, is cooled via cooler 3008, with effect that a mixed fluid second solvent-rich intermediate precursor 3065 is Date recue / Date received 2021-11-30 obtained, and the gaseous third solvent-rich fraction 3061, or a derivative thereof, is cooled via cooler 3009, with effect that a mixed fluid solvent-rich intermediate precursor 3066 is obtained. At least the mixed fluid first solvent-rich intermediate precursor 3064, mixed fluid second solvent-rich intermediate precursor 3065, and the mixed fluid third solvent-rich intermediate precursor 3066 are admixed with effect that a mixed fluid solvent-rich intermediate 3067 is produced.

[0050] In some embodiments, for example, a separable solvent-rich fluid intermediate 3067A, derived from the mixed fluid solvent-rich fluid intermediate 3067, is separated, via gravity separation, into at least a recovered liquid solvent-rich fraction 3068, a recovered water-rich fraction 3069, and a recovered gaseous non-condensable material 3070. The gravity separation is effected within the condensate drum 3010.

[0051] In some embodiments, for example, a recycled solvent material 2041, derived from the recovered liquid solvent-rich fraction 3068, is recycled to the froth treatment unit 230, such that at least a fraction of the solvent material 204 includes the recycled solvent material 2041. In some embodiments, for example, the recycled solvent material 2041 is the recovered liquid solvent-rich fraction 3068.

[0052] In some embodiments, for example, a recycled process water, derived from the recovered water-rich fraction 3069, is recycled for use within the process configuration. In some embodiments, for example, the recycled process water is the recovered water-rich fraction 3069.

[0053] In some embodiments, for example, gaseous non-condensable material product, derived from the recovered gaseous non-condensable material 3070, is vented to a vapour recovery unit ("VRU") 3071 for effecting recovery of valuable hydrocarbon material from the gaseous non-condensable material. In Date recue / Date received 2021-11-30 some embodiments, for example, gaseous non-condensable material product is the recovered gaseous non-condensable material 3070. In this respect, in some embodiments, for example, the recovered gaseous non-condensable material 3070 defines a one of the one or more product material outputs.

[0054] In some embodiments, the components of the system 10 downstream from the froth deaerator 220 can be referred to as a secondary bitumen production facility 200, as distinct from the primary bitumen production facility 100.

[0055] The processing of the bitumen-comprising material, via the original process configuration, is characterized by at least one process parameter, wherein each one of the at least one process parameter, independently, has a value, and such value is represented by a process parameter value, such that at least one process parameter value is established. In this respect, associated with the processing of the bitumen-comprising material, is process parameter information 230, and the process parameter information 230 includes at least one process parameter value.

[0056] Each one of the at least one process parameter, independently, is representative of a parameter of the original process configuration. Exemplary parameters include one or more characteristics of the bitumen ore 12, and/or one or more conditions of the processes described above as part of the system 10.
Further exemplary process parameters of the process configuration are described below with reference to FIGs 3A and 3B.

[0057] A method for processing bitumen-comprising material, derived from a bitumen ore, is provided, and the method includes obtaining the process parameter information 130. In some embodiments, for example, the obtaining of the process parameter information includes obtaining process parameter information via Date recue / Date received 2021-11-30 sensors. The obtaining of process parameter information is further elaborated below.

[0058] The obtained process parameter information is processed, using a trained prediction machine learning model, to predict a hydrogen sulphide concentration measure of a processed material. The hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material. The processed material is defined by a one of the one or more derivative materials. In this respect, in some embodiments, for example, the processed material is a product material being discharged from the process configuration. As well, in some embodiments, for example, the processed material is an intermediate material.

[0059] Based on the hydrogen sulphide concentration measure, the original process configuration is modified, such that a modified process configuration is established. While the bitumen-comprising material is being processed via the modified process configuration, a modified processed material, derived from the bitumen-comprising material, and corresponding to the processed material established during the processing by the original process configuration, is established during the processing by the modified process configuration. The modifying of the original process configuration is with effect that a concentration of hydrogen sulphide of the modified processed material, established by the processing of the bitumen-comprising material by the modified process configuration, is less than the concentration of hydrogen sulphide of the original processed material established by the processing of the bitumen-comprising material by the original process configuration.

[0060] Exemplary modifications to the original process configuration include modifications to the process conditions, such as, for example, an operating temperature within the process configuration, or a flowrate of a derivative material.
Date recue / Date received 2021-11-30 Another exemplary modification is a modulation (initiation, increase, decrease, or suspension) to chemical addition to the process configuration, such as, for example, the injection of a H2S scavenger. Exemplary modifications are further discussed below.

[0061] An example process control module 310 will now be described that can be used to predict H2S events and mitigate the severity and/or the effects of events. A prediction machine learning model 314 is trained to predict H2S
events using training data 326 based on historical process parameter information 320, thereby establishing a trained prediction machine learning model 314A. The trained prediction machine learning model 314A is used to predict H2S events, generating prediction information potentially including a prediction of the timing, location, and/or severity thereof as indicated by at least an H2S concentration measure 316.
In some embodiments, an operator of the system 10 is alerted to the prediction information, including the H2S concentration measure 316. In some embodiments, an H2S mitigation module 318 is used to process the prediction information, including the H2S concentration measure 316, to generate recommended process parameter information 322, which can be used by one or more human operators and/or one or more automatic processes to modify the process configuration to mitigate the predicted H2S event.

[0062] The processed material can be material processed at any stage of the process configuration. For example, in bitumen ore processing systems 10, the recovered gaseous non-condensable material 3070, supplied to the VRU 3071, is prone to high concentrations of H2S. Thus, in some examples, the processed material established by the processing of the bitumen-comprising material by the original process configuration is an original recovered gaseous non-condensable material 3070 having a relatively high H2S concentration measure 316. Using the methods and systems described herein, the H2S concentration measure 316 of the Date recue / Date received 2021-11-30 recovered gaseous non-condensable material 3070 can be predicted and mitigated by generating recommended process parameter information 322 suitable to establish a modified process configuration. The modified process configuration modifies process parameters of the process configuration of the system 10, such as, for example, parameters that govern the flow rate of the derivative material and/or temperature within the process configuration, and/or an amount of a chemical additive (such as a H2S scavenger material) injected into the process configuration. When the bitumen-comprising material begins to be processed via the modified process configuration, a modified processed material (i.e. a modified recovered gaseous non-condensable material 3070) is established having a lower concentration of H2S (i.e. a lower H2S concentration measure 316) than the original processed material (i.e. the original recovered gaseous non-condensable material 3070).

[0063] Existing strategies (e.g. amine injection), for mitigating H2S
events, are based upon feedback control strategies, which are innplennentable only after the H2S event has occurred, such that the mitigation is an ex post facto mitigation of H2S concentration. For example, an exemplary one of an existing strategy is to manually measure pH or iron content (indicative of H2S-related corrosion of metal equipment) of the recovered water-rich fraction 3069, which measurement might be made infrequently (such as once or twice a day). The infrequency of measurement, and the nature of the measurement, means that H2S concentration may be high within the system 10 for many hours before mitigation steps can be taken. Furthermore, because the evolution of generation of H2S from bitumen-comprising material is a function of factors, including the thermal history of the material, mitigation of H2S events after the fact typically means that the bitumen-comprising material has already been subject to processing that predisposes it to H2S generation, which cannot be undone.
Date recue / Date received 2021-11-30

[0064] In contrast, proactive machine learning-based techniques, such as example embodiments described herein, provide a means by which mitigating steps can be taken at earlier stages in the processing of the bitumen-comprising material, and prior to H2S concentration rising to undesirable levels.

[0065] In some embodiments, for example, by using a prediction model to predict H2S events before H2S concentration reaches dangerous levels, a suitable mitigation strategy can be performed prospectively or prophylactically so as to prevent H2S generation before H2S concentration levels become elevated. Thus, example embodiments described herein therefore have the potential to effect much more effective and more efficient mitigation of H2S events than existing approaches relying on ex post facto strategies.

[0066] For example, in some embodiments, mitigation steps include addition of an H2S scavenger to the process configuration where an unacceptably high concentration is present. In some embodiments, for example, the H2S scavenger is an amine material, such as, for example, nnonoethanolannine. In some embodiments, for example, an amine material is sprayable into the overhead (i.e.
the gaseous fraction) of the flash drum 3001, or into the gaseous first solvent-rich fraction 3061 recovered therefrom, in order to reduce the H2S concentration of the gaseous material within the VRU 3071.

[0067] For example, in some embodiments, for example, mitigation steps include modulating (i.e. increasing or decreasing) a fractionation temperature parameter representative of the operating temperature within one of the fractionation stages within the solvent recovery unit 300 (such as, for example, the temperature in one or more of zones 3001A, 3002A, and 3003A). In some embodiments, for example, reducing such temperature mitigates cracking of nnercaptan material within the material being processed, thereby mitigating the Date recue / Date received 2021-11-30 formation of H2S, which is a reaction product of the cracking of nnercaptan material.

[0068] Mercaptan material is defined by at least one nnercaptan compound.
Each one of the at least one nnercaptan compound, independently, is of formula (I):
R-S-H
wherein R is an organic group.

[0069] In some embodiments, for example, it is desirable for the temperature of the liquid recovered bitumen-rich fraction 302 to be less than 130 degrees Celsius, so as to mitigate production of H2S via cracking of nnercaptan material that is present within the liquid recovered bitumen-rich fraction 302. Production of excessive H2S in such case could overpressurize storage tanks 3011 within which the liquid recovered bitumen-rich fraction 302, or its derivative, is contained, and thereby compromise the integrity of such storage tanks 3011, potentially resulting in their failure and causing release of the generated H2S.

[0070] In some embodiments, for example, increasing the rate of flow of material to be processed by the solvent recovery unit 300 (e.g. the bitumen-rich fractionatable material 304) reduces the duration of time, spent by the material, exposed to relatively high temperatures (greater than 130 degrees Celsius), which promotes the cracking of nnercaptan material resident within the processed material (and leads to the evolution of H2S). In this respect, in some embodiments, for example, For example, in some embodiments, for example, mitigation steps include modulating (i.e. increasing or decreasing) a froth volume parameter representative of a rate of flow of the bitumen-rich froth overflow 104, and/or a parameter representative of a rate of flow of the bitumen-rich froth overflow feed 105, and/or a parameter representative of a rate of flow of the de-aerated bitumen-rich intermediate 221, and/or a parameter representative of a rate of flow of the de-Date recue / Date received 2021-11-30 aerated bitumen-rich intermediate feed 202, and/or a parameter representative of a rate of flow of the bitumen-rich separation fraction 208, and/or a parameter representative of a rate of flow of the bitumen-rich fractionatable material 304.

[0071] For example, in some embodiments, for example, mitigation steps include modulating (i.e. increasing or decreasing) a froth volume parameter representative of a rate of flow of the bitumen-rich froth overflow 104, and/or a parameter representative of a rate of flow of the bitumen-rich froth overflow feed 105, and/or a parameter representative of a rate of flow of the de-aerated bitumen-rich intermediate 221, and/or a parameter representative of a rate of flow of the de-aerated bitumen-rich intermediate feed 202, and/or a parameter representative of a rate of flow of the bitumen-rich separation fraction 208, and/or a parameter representative of a rate of flow of the bitumen-rich fractionatable material 304.

[0072] In some embodiments, for example, the H2S concentration within the system 10 is reduced by a combination of increasing the rate of flow of material to be processed by the solvent recovery unit 300 (e.g. the bitumen-rich fractionatable material 304) and decreasing the operating temperature within one or more of the fractionation stages (such as, for example, the zone 3003A of the flash drum 3003). Modulating both of these process parameters, in tandem, has a greater effect than the sum of the effects of modulating each parameter in isolation.

[0073] In some embodiments, for example, mitigation steps include modulating the source of bitumen ore, such that bitumen ore 12 is supplied from a different source (or a different mix of bitumen ores from different sources).
For example, specific types of bitumen ore 12 are more prone to generation of H2S
during processing, and the process configuration can be modified to supply a mix of bitumen ore 12 to the system 10 that contains a smaller proportion of H2S-prone bitumen ore types than the original process configuration.
Date recue / Date received 2021-11-30

[0074] FIG. 2 is a block diagram of an example computing system 240 including computing hardware suitable for predicting and mitigating H2S
generated in bitumen processing according to example embodiments described herein. In some implementations, computing system 240 can be an electronic computing device, such as a networked server. In other implementations, the computing system 240 can be a distributed computing system including multiple devices (such as a cloud computing platform) or a virtual machine running on one or more devices in mutual communication over a network. Other examples suitable for implementing implementations described in the present disclosure can be used, which can include components different from those discussed below. Although FIG.
2 shows a single instance of each component, there can be multiple instances of each component in the computing system 240.

[0075] The computing system 240 can include one or more processor devices (collectively referred to as processor device 242). The processor device 242 can include one or more processor devices such as a processor, a microprocessor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a dedicated logic circuitry, a dedicated artificial intelligence processor unit, or combinations thereof.

[0076] The computing system 240 can include one or more network interfaces (collectively referred to as network interface 246) for wired or wireless communication over a network. The network interface 246 can include wired links (e.g., Ethernet cable) and/or wireless links (e.g., one or more antennas). The computing system 240 can communicate with one or more user devices 247 (such as user workstation computers) via the network interface 246. The computing system 240 can also communicate with various sensors 248 or other data sources to obtain data used in monitoring and/or operating the bitumen ore processing system 10, such as sensors 248 or data sources supplying process parameter Date recue / Date received 2021-11-30 information 320. In some embodiments, the sensors 248 can include H2S sensors located at various stages within the bitumen ore processing system 10: for example, gas chromatography sensors can be located at a mine surface (e.g.
proximate to one or more shovels excavating an open pit), within an ore processing plant (OPP) (for example, proximate to ore crushers converting the bitumen ore into size-reduced bitumen ore 20), within the froth deaerator 220, within various components of the solvent recovery unit (SRU) 300, or within the VRU 3071, within the storage tanks 3011 used to store the bitumen product material (i.e. the recovered bitumen-rich fraction 302), and/or at any other location within the bitumen ore processing system 10 where H2S gas is likely to be generated or accumulate. In some embodiments, additional sensors 248 can be used to detect secondary effects of H2S, such as pH sensors used to detect the pH of liquid material and/or iron sensors to detect the presence of iron in liquid material at one or more locations or stages (such as recovered water-rich fraction 3069).
Iron, detected within the liquid materials of the system 10, is indicative of corrosion of the metal equipment of the bitumen ore processing system 10. In some embodiments, one or more of the aforementioned measurements (e.g., gas chromatography, liquid pH, liquid iron content) can be performed using an offline sensor or test and manually entered into the computing system 240, for example by personnel operating a user device 247.

[0077] The computing system 240 can also communicate with various process controllers 249 via the network interface 246 to control the process parameters of the process configuration (e.g., the primary bitumen production facility 100 including the primary froth flotation circuit 120 and the secondary froth flotation circuit 130, the froth deaerator 220, and the secondary bitumen production facility 200 including the froth treatment unit 230 and the solvent recovery unit 300).
In some examples, the user devices 247 and/or the components of the process Date recue / Date received 2021-11-30 configuration can communicate with the computing system 240 through other means, such as an input/output interface of the computing system 240 (not shown) or through an intermediate device in communication with the computing system 240.

[0078] The computing system 240 can include one or more non-transitory memories (referred to collectively as a memory 244), which can include a volatile or non-volatile memory (e.g., a flash memory, a random access memory (RAM), and/or a read-only memory (ROM)). The memory 244 can also include one or more mass storage units, such as a solid state drive, a hard disk drive, a magnetic disk drive and/or an optical disk drive.

[0079] The memory 244 can store instructions for execution by the processor device 242 to carry out examples described in the present disclosure. The instructions can include instructions for implementing and operating the process control module 310 described below with reference to FIG.s 3A-3B. The memory 244 can include other software instructions, such as for implementing an operating system and other applications/functions. In some examples, the computing system 240 can additionally or alternatively execute instructions from an external memory (e.g., an external drive in wired or wireless communication with the computing system 240) or can be provided executable instructions by a transitory or non-transitory computer-readable medium. Examples of non-transitory computer readable media include a RAM, a ROM, an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a CD-ROM, or other portable memory storage.

[0080] The memory 244 can store data and models used by the process control module 310. Process parameter information 320, as described below with reference to FIG. 3B, can be stored in the memory. Models used by the process control module 310, such as models trained using machine learning (ML) algorithms Date recue / Date received 2021-11-30 (as described below with reference to FIG. 3A), can be considered to be stored in the memory 244 as part of the process control module 310. The memory 244 can also store other information or data used in training the models of the process control module 310, such as training data 326 (as described with reference to FIG.
3A), and/or other information or data used in executing the process control module 310 (such as preprocessed data generated by the data preprocessing subnnodule 312 of FIG. 3B).

[0081] The computing system 240 can also include a bus 250 providing communication among components of the computing system 240, including those components discussed above. The bus 250 can be any suitable bus architecture including, for example, a memory bus, a peripheral bus or a video bus, or the bus 250 can be another communication link such as a network interface 246.

[0082] FIG.s 3A-3B illustrate an example process control module 310.
The process control module 310 is executed by a computing system 240 to perform the methods and operations described herein. The process control module 310 includes a number of functional components 312, 314, 317, 318, as described below. It will be appreciated that some implementations can omit one or more of the described components and/or can combine the functions of two or more of the described components into a single component. In some implementations, different functions of the process control module 310 can be performed on different devices other than the computing system 240. For example, computationally intensive functions such as training machine learning models and executing trained machine learning models can be performed on a cloud computing platform in communication with a local computing system 240.

[0083] In some implementations, the process control module 310 operates to predict and/or mitigate H2S events in the bitumen ore processing system 10. It will be appreciated that similar process control modules 310 could be configured, Date recue / Date received 2021-11-30 trained, and deployed to predict or mitigate H2S concentration in another type of bitumen processing system.

[0084] FIG. 3A shows the process control module 310 operating in a training mode in order to train the machine learning models used by the process control module 310. The process control module 310 includes a prediction machine learning model 314 which must be trained using machine learning algorithms before the process control module 310 can be executed to predict or mitigate H2S events in the bitumen ore processing system 10 in a deployment mode (as shown in FIG.
3B).

[0085] During training mode, the process control module 310 uses a prediction model training subnnodule 317 to train the prediction machine learning model 314. A training dataset, consisting of training data 326, can be used to train the prediction machine learning model 314 using any of a number of machine learning techniques, such as supervised, unsupervised, or semi-supervised learning techniques. In some embodiments, the prediction machine learning model 314 includes an artificial neural network trained using supervised learning.

[0086] In some embodiments, the prediction machine learning model 314 includes a neural network, such as a multi-layer perceptron neural network, which is trained by the prediction model training subnnodule 317 using back-propagation to generate a trained prediction machine learning model 314A (shown in FIG.
3B).
The training data 326 includes semantically labelled data samples, such as preprocessed samples of historical process parameter information 320, each data sample being labelled with a ground truth H2S concentration measure associated with the historical process parameter information 320. The data samples are .. provided as input to the prediction machine learning model 314, which processes these inputs to generate a predicted H2S concentration measure 316. In some embodiments, the predicted H2S concentration measure 316 includes a predicted Date recue / Date received 2021-11-30 concentration of H2S of at least one gaseous or liquid material within the process configuration. In some embodiments, the predicted H2S concentration measure includes a predicted concentration of H2S of the recovered bitumen-rich fraction 302 (e.g. the liquid bitumen product output of the secondary bitumen production facility 200). In some embodiments, the predicted H2S concentration measure includes a predicted concentration of H2S of the recovered gaseous non-condensable material 3070.

[0087] The prediction model training subnnodule 317 compares the predicted H2S concentration measure 316 to the ground truth H2S concentration measure obtained from the training data 326, computes a loss based on the comparison, and back-propagates the computed loss through the layers of neurons of the prediction machine learning model 314 using gradient descent to adjust the learned parameter values of the learnable parameters of the prediction machine learning model 314. This process can be repeated over one or more training epochs until the learned parameter values of the prediction machine learning model 314 converge, or until another training termination criterion is satisfied, in accordance with known machine learning techniques. Once training terminates, the prediction machine learning model 314 is considered to be a trained prediction machine learning model 314A, and is ready for deployment in a deployment mode, as described with reference to FIG. 3B.

[0088] It will be appreciated that other types of models, trained using machine learning techniques (also called "machine learning models"), can be used in some embodiments to implement the prediction machine learning model 314 and/or the H2S mitigation module 318 described below with reference to FIG.
3B.

[0089] The training data 326 can be generated using historical operating data from a bitumen ore processing system 10. The data samples used to train the prediction machine learning model 314 can be generated by storing samples of Date recue / Date received 2021-11-30 actual process parameter information corresponding to the process configuration of the bitumen ore processing system 10 during operation. The actual H2S
concentration measure 316 of the bitumen ore processing system 10, resulting from the operation of the system 10 according to the process configuration, is stored as a semantic label associated with the data sample.

[0090] In some embodiments, for example, the data samples of the training data 326 include process parameter information (such as ore information and process condition information) that has been preprocessed, as described with reference to FIG. 3B below. Some process parameters of the process parameter information 320 can be computed based on one or more data inputs, such as sensor readings from one or more sensors 248 configured to sense process conditions and/or ore characteristics at various locations or within various sub-systems of the ore processing system 10, laboratory data from one or more laboratory tests performed on the ore, and/or other data inputs from other data sources.

[0091] In some embodiments, the process parameter information 320 includes, for each one of one or more process parameters, a value. In some embodiments, for example, the one or more process parameters include one or more ore characteristic parameters and/or one or more process condition parameters. Each of the one or more process parameters, independently, is representative of a respective characteristic of the supplied ore and/or respective process condition of the process configuration. The ore characteristic parameters can be measured or estimated using geological models, survey data, laboratory testing data, sensor data, etc. The process condition parameters can be measured based on process control equipment settings, sensor data, etc.

[0092] In some embodiments, for example, the one or more process condition parameters can include flow rates of various streams of material at various stages Date recue / Date received 2021-11-30 within the process configuration, pressures and/or temperatures of various streams of material at various stages within the process configuration, and/or other parameters representative of conditions of the process configuration, as measured or estimated using equipment setting data for equipment used in the process configuration, sensor data from sensors 248 configured to monitor process conditions within the process configuration.

[0093] The one or more process parameters can include one or more process parameters of the process configuration which defines the primary bitumen production facility 100. This includes a bitumen ore type parameter representative of a type of the bitumen ore; a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the bitumen ore 12, a surge pile level parameter representative of a volume of bitumen ore 12 in a surge pile of an ore feed source (e.g. an ore preparation plant), an ore feed parameter representative of a rate of supply of bitumen ore 12 from an ore feed source, being processed by the process configuration, a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the multi-phase bituminous admixture 14, a froth volume parameter representative of a rate of flow of the bitumen-rich froth overflow 104, a middling density parameter representative of a middling density of the middlings product 108, a past-hour froth volume parameter representative of a volumetric flow rate of the de-aerated bitumen-rich intermediate, 221, or of a volumetric flow rate of the de-aerated bitumen-rich intermediate feed 202, over the past hour of operation (or other period of time), a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the gaseous discharge from the de-aeration operation of the froth de-aerator 220.

[0094] The one or more process parameters can include one or more process parameters of the process configuration which defines the secondary bitumen Date recue / Date received 2021-11-30 production facility 200. This includes a bitumen-rich separation fraction flowrate representative of a rate of flow of the bitumen-rich separation fraction 208;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the liquid bitumen-rich product material (e.g. bitumen-rich recovered fraction 302); a liquid bitumen-rich product material flowrate representative of a rate of flow of the liquid bitumen-rich product material (e.g.
bitumen-rich recovered fraction 302); a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of a gaseous material being processed within the solvent recovery unit 300 (e.g. H2S concentration of a respective one or more of materials 3061, 3062, 3063, 3064, 3065, 3066, 3067, 3067A, and 3070); a solvent recovery flowrate parameter representative of a rate of flow of the gaseous material being processed within the solvent recovery unit 300 (e.g. the rate of flow of a respective one or more of materials 3061, 3062, 3063, 3064, 3065, 3066, 3067, 3067A, and 3070); and an operating temperature of a unit operation within the solvent recovery unit 300 (e.g. the flash drum 3001, the distillation column 3002, the flash drum 3003, or the condensate drum 3010).

[0095] FIG. 3B shows the operation of the process control module 310 in a deployment mode, after the prediction machine learning model 314 has completed training such that the prediction machine learning model 314 constitutes a trained prediction machine learning model 314A. In deployment mode, the process control module 310 is effective to monitor process parameter information 320 and to optimize the processing of bitumen ore by adjusting the controllable process parameter values of the process configuration, accordingly. The optimization process performed by the process control module 310 in deployment mode can be performed in real time while the bitumen ore 12 is being processed.

[0096] In deployment mode, the process control module 310 includes an mitigation module 318. In some embodiments, the H2S mitigation module 318 uses Date recue / Date received 2021-11-30 a brute force optimization algorithm to optimize a set of controllable process parameters, i.e. process parameters that can be used to define a modified process configuration that can be effected by an operator of the system 10. In some embodiments, the brute force optimization algorithm uses an exhaustive search algorithm to traverse the combinatorial search space of possible controllable process parameter values. In other embodiments, another search algorithm can be used to traverse the combinatorial search space of possible controllable process parameter values, such as a random walk optimization algorithm. At each step of traversing the combinatorial search space of possible controllable process parameter values, the H2S mitigation module 318 provides the set of controllable process parameter values being evaluated into the trained prediction machine learning model 314A and seeks to identify a set of controllable process parameter values that effectively mitigates the predicted H2S concentration measure 316 generated by the trained prediction machine learning model 314A. The identified set of controllable process parameters, alone or in combination with other process parameters, are referred to herein as recommended process parameters information 322, and can be subsequently used to define a modified process configuration. When the recommended process parameters information 322 is identified by the H2S mitigation module 318, the recommended process parameter information 322 is output by the H2S mitigation module 318.

[0097] In some embodiments, the recommended process parameter information 322 is used to modify the original process configuration to establish a modified process configuration. Each of the one or more controllable process parameters of the recommended process parameter information 322 is representative of a respective process parameter used to control the operation of the ore processing system 10. In some embodiments, for example, modification of the original process configuration includes one or more H2S-mitigating steps as Date recue / Date received 2021-11-30 described above. Thus, in some embodiments, for example, modification of the original process configuration can include one or more of the following:
modulating (i.e. initiating, increasing, decreasing, or suspending) supply of a scavenger (such as a H2S scavenger material) into the process configuration; modulating (i.e.
initiating, increasing, decreasing, suspending) a pH of the original processed material, modulating (i.e. initiating, increasing, decreasing, suspending) supply of an amine to the process configuration, modulating (i.e. increasing or decreasing) a parameter representative of a rate of flow of a material being processed through the process configuration (such as, for example, one or more of material flows 104, 105, 221, 202, 208, and 304), modulating (i.e. increasing or decreasing) a fractionation temperature parameter representative of the operating temperature within one of the fractionation stages within the solvent recovery unit 300 (such as, for example, the temperature in one or more of zones 3001A, 3002A, and 3003A), modulating the source of bitumen ore, such that bitumen ore 12 is supplied from a different source (or a different mix of bitumen ores from different sources), and/or modifying other process parameters representative of operating settings or control settings of the bitumen ore processing system 10, as indicated by equipment setting data for equipment used in the bitumen ore processing system 10, or from sensor data from sensors 248 configured to monitor equipment settings and conditions within the bitumen ore processing system 10.

[0098] In deployment mode, the process control module 310 obtains process information in real time based on the process parameters defining the original process configuration of the bitumen ore processing system 10. A data preprocessing module 312 obtains and pre-processes the process parameter information to generate preprocessed data suitable for use as input to the trained prediction machine learning model 314A and H2S mitigation module 318. For example, the data preprocessing module 312 can compute one or more additional Date recue / Date received 2021-11-30 process parameters based on one or more ore characteristic parameters and/or one or more process condition parameters.

[0099] The preprocessed data is provided as input to the trained prediction machine learning model 314A, which processes the inputs to predict the H2S
concentration measure 316. The preprocessed data is also provided as input to the H2S mitigation module 318, along with the predicted H2S concentration measure 316. The H2S mitigation module 318 processes its inputs to obtain recommended process parameter information 322, such that the recommended process parameter information 322 establishes a modified process configuration effective to mitigate the H2S concentration measure 316, as described above.

[0100] The recommended process parameter information 322 can be used in one or more ways to mitigate H2S events within the bitumen ore processing system 10. In some embodiments, the process configuration of the bitumen ore processing system 10, or of a sub-system thereof, can be modified by the process control module 310 based on the recommended process parameter information 322 such that a modified process configuration is obtained. In some embodiments, the recommended process parameter information is presented to an operator of the process configuration via an output device, such as a user device 247 (e.g., a workstation with a display device). Details of the co-operation of the process control module 310 with the bitumen ore processing system 10 are described in detail below with reference to the method of FIG. 4.

[0101] Example implementations of methods for processing ore (such as bitumen ore) will now be described, with reference to the example process control module 310 executed by the example computing system 240 in co-operation with the bitumen ore processing system 10.
Date recue / Date received 2021-11-30

[0102] FIG. 4 is flowchart showing operations of a method 400 for processing bitumen-comprising material derived from a bitumen ore.

[0103] At 402, the bitumen ore processing system 10 processes the bitumen-comprising material via an original process configuration such that an original processed material (e.g., the bitumen-rich froth overflow 104, or the bitumen-rich fraction 302) is produced. In some embodiments, for example, as described above, the bitumen-comprising material is any one of the bitumen-comprising materials identified in FIG. 1A or FIG. 1B, such as those identified by any one of the following reference numerals: 12, 20, 14, 102, 104, 106, 108, 112, 114, 221, 202, 231, 232, 210, 208, 304, 3021, 3022, 3023, 3024, and 302). The original processed material is any material that is derived from the bitumen-comprising material. In some embodiments, for example, the original processed material includes H2S. In some embodiments, for example, the original processed material includes those materials identified in FIG 1A or FIG 1B, such as those identified by any one of the following reference numerals: 20, 14, 102, 104, 106, 108, 112, 114, 221, 202, 231, 232, 210, 208, 304, 3021, 3022, 3023, 3024, 302, 3061, 3062, 3063, 3064, 3065, 3066, 3067, 3070, 3068).

[0104] While the bitumen-comprising material is being processed at 402, the method 400 proceeds to steps 404 to 416.

[0105] At 404, process parameter information is obtained by the process control module 310 (e.g., by the data preprocessing subnnodule 312).

[0106] At 408, the process parameter information is processed using the trained prediction machine learning model 314A (e.g., mediated by the data preprocessing subnnodule 312), to predict the H2S concentration measure 316 of the process configuration.
Date recue / Date received 2021-11-30

[0107] At 410, the process parameter information 320 and the H2S
concentration measure 316 predicted by the trained prediction machine learning model 314A are processed using the H2S mitigation module 318 (e.g., mediated by the data preprocessing subnnodule 312), such that the recommended process parameter information 322 is obtained.

[0108] At 412, optionally, the process control module 310 modifies the original process configuration based on the recommended process parameter information 322 such that a modified process configuration is obtained. In some embodiments, step 412 therefore includes modulating one or more process parameters of the process configuration (i.e. the controllable process parameters of the bitumen ore processing system 10), based on the recommended process parameter information 322, such that the modified process parameter configuration is obtained.

[0109] At 414, optionally, the recommended process parameter information .. 322 is presented to an operator of the process configuration via an output device, such as a user device 247 including a display. In some examples, the computing system 240 generates a user output screen showing recommended process parameter values based on the recommended process parameter information 322.
The computing system 240 transmits the user output screen to the user device 247, such as a user workstation, which displays the user output screen on a display of the workstation. An operator of the process configuration (e.g., a worker in the control room of the primary bitumen production facility 100 or the secondary bitumen production facility 200) can review the recommended process parameters shown on the user output screen and, in some embodiments, can use the user device 247 to set the values of one or more of the controllable process parameters to the recommended values or to other, user-selected, values. The selected values of the controllable process parameters can be implemented in the operation of the Date recue / Date received 2021-11-30 bitumen ore processing system 10 (or a sub-system thereof, such as the primary bitumen production facility 100 or the secondary bitumen production facility 200) directly using one or more process controllers in communication with the user device 247 and/or indirectly by communicating the selected value to another worker, who in turn implements the selected value(s) by adjusting equipment or other components of the bitumen ore processing system 10.

[0110] At 416, the bitumen ore processing system 10 processes another portion of the bitumen-comprising material using the modified process configuration.

[0111] It will be appreciated that, in some examples, method 400 may omit steps 410, 412, 414, and/or 416, and may simply operate to predict the H2S
concentration measure 316. Separate methods or processes may then be initiated in response to the predicted H25 concentration measure 316.

[0112] In some embodiments, the process control module 310, including the trained prediction machine learning model 314A and the H25 mitigation module 318, can be used to identify relationships between process parameters that can be exploited to mitigate or reduce H25 concentration within the system 10 on an ongoing basis without the need for real-time deployment of the process control module 310. For example, as described above, testing of the process control module 310 has shown that various mitigation steps can be effective in mitigating or decreasing H25 concentration levels. Exemplary mitigation steps are discussed above. Whereas the unpredictable frequency of H25 events makes it difficult to fully and effectively mitigate H25 events without use of the trained prediction machine learning model 314A, in some examples one or more of the mitigations steps described above can be implemented on an ongoing basis to mitigate a baseline amount of H25 generated within the system 10.
Date recue / Date received 2021-11-30 General

[0113] Although the present disclosure describes functions performed by certain components and physical entities, it should be understood that, in a distributed system, some or all of the processes can be distributed among multiple components and entities, and multiple instances of the processes can be carried out over the distributed system.

[0114] Although the present disclosure describes methods and processes with steps in a certain order, one or more steps of the methods and processes can be omitted or altered as appropriate. One or more steps can take place in an order other than that in which they are described, as appropriate.

[0115] Although the present disclosure is described, at least in part, in terms of methods, a person of ordinary skill in the art will understand that the present disclosure is also directed to the various components for performing at least some of the aspects and features of the described methods, either by way of hardware components, software or any combination of the two. Accordingly, the technical solution of the present disclosure can be embodied in the form of a software product. A suitable software product can be stored in a pre-recorded storage device or other similar non-volatile or non-transitory computer readable medium, including DVDs, CD-ROMs, USB flash disk, a removable hard disk, or other storage media, for example. The software product includes instructions tangibly stored thereon that enable a processing device (e.g., a personal computer, a server, or a network device) to execute examples of the methods disclosed herein. In general, the software improves the operation of the hardware in one or more ways.

[0116] The present disclosure can be embodied in other specific forms without departing from the subject matter of the claims. The described example implementations are to be considered in all respects as being only illustrative and Date recue / Date received 2021-11-30 not restrictive. Selected features from one or more of the above-described implementations can be combined to create alternative implementations not explicitly described, features suitable for such combinations being understood within the scope of this disclosure.

[0117] All values and sub-ranges within disclosed ranges are also disclosed.
Also, although the systems, devices and processes disclosed and shown herein can include a specific number of elements/components, the systems, devices and assemblies could be modified to include additional or fewer of such elements/components. For example, although any of the elements/components disclosed can be referenced as being singular, the implementations disclosed herein could be modified to include a plurality of such elements/components. The subject matter described herein intends to cover and embrace all suitable changes in technology.
Date recue / Date received 2021-11-30

Claims (39)

- 51 -

1. A method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;
wherein:
the process parameter information includes at least one process parameter value;
each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
processing the process parameter information, using a trained prediction machine learning model, to predict a hydrogen sulphide concentration measure of a processed material, defined by one of the one or more derivative materials, wherein the hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material;
and based on the hydrogen sulphide concentration measure, modifying the original process configuration, such that a modified process configuration is established;
wherein:
the a concentration of hydrogen sulphide of the processed material, established by the processing of the bitumen-comprising material by the modified process configuration, is less than the concentration of hydrogen sulphide of the processed material established by the processing of the bitumen-comprising material by the original process configuration.

2. The method as claimed in claim 1;

wherein:
the hydrogen sulphide concentration measure is a concentration of hydrogen sulphide of the processed material.

3. The method as claimed in claim 2;
wherein:
the processing via the original process configuration includes:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth overflow intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth overflow is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;

admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least a solvent-conditioned bitumen-rich separation fraction and a solids-rich separation fraction; and within a solvent recovery unit, fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility;
and the hydrogen sulphide concentration measure includes at least one of:
(i) a hydrogen sulphide concentration of the liquid recovered bitumen-rich fraction; and (ii) a hydrogen sulphide concentration of gaseous material derived from the gaseous recovered solvent-rich fraction.

4. The method as claimed in claim 3;
wherein:
the solvent material includes paraffinic solvent.

5. The method as claimed in claim 3 or 4;
wherein:
the at least one process parameter includes at least one of:
a bitumen ore type parameter representative of a type of the bitumen ore;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the bitumen ore;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the multi-phase bituminous admixture;
a froth volume parameter representative of a rate of flow of the bitumen-rich froth overflow;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the gaseous deaeration operation output material;
a fractionatable bitumen-rich separation fraction flowrate representative of a rate of flow of the fractionatable bitumen-rich separation fraction;
a fractionation temperature parameter representative of a temperature at which the fractionatable bitumen-rich separation fraction is being fractionated;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the liquid bitumen-rich product material;
a liquid bitumen-rich product material flowrate representative of a rate of flow of the liquid bitumen-rich product material;
a temperature parameter representative of the temperature of the liquid bitumen-rich product material;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of gaseous material derived from the gaseous solvent-rich output material; and a solvent recovery flowrate parameter representative of a rate of flow of the gaseous solvent-rich output material.

6. The method as claimed in any one of claims 3 to 5;
wherein:
the bitumen ore is derived from a surge pile; and the at least one process parameter includes a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of a gaseous environment disposed in mass transfer communication with the surge pile.

7. The method as claimed in any one of claims 3 to 6;
wherein:
the modifying of the original process configuration includes at least one of:
modulating supply of a bitumen ore, having a bitumen ore type indicated by the bitumen ore type parameter, into the process configuration;
modulating the rate of flow of the bitumen-rich separation fraction into the solvent recovery unit;
and modulating the temperature at which the fractionatable bitumen-rich separation fraction is being fractionated

8. The method as claimed in any one of claims 1 to 6;
wherein:
the modifying of the original process configuration includes modulating supply of a scavenger into the process configuration.

9. The method as claimed in any one of claims 1 to 8;
wherein:
the modifying of the original process configuration includes modulating pH of the original processed material.

10. The method as claimed in claim 9;
wherein:
the modulating includes modulating supply of an amine material to the process configuration.

11. The method as claimed in any one of claims 1 to 10;
further comprising:
processing the bitumen-comprising material via the modified process configuration.

12. A method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;

wherein:
the process parameter information includes at least one process parameter value;
each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
processing the process parameter information, using a trained prediction machine learning model, to predict a hydrogen sulphide concentration measure of a processed material, defined by one of the one or more derivative materials, wherein the hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material;
and based on the hydrogen sulphide concentration measure, modifying the original process configuration with effect that the concentration of hydrogen sulphide of the processed material is reduced, such that a modified processed material is established.

13. The method as claimed in claim 12;
wherein:
the hydrogen sulphide concentration measure is a concentration of hydrogen sulphide of the processed material.

14. The method as claimed in claim 13;
wherein:
the processing via the original process configuration includes:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth overflow intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth overflow is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least a solvent-conditioned bitumen-rich separation fraction and a solids-rich separation fraction; and within a solvent recovery unit, fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility;
and the hydrogen sulphide concentration measure includes at least one of:
(iii) a hydrogen sulphide concentration of the liquid recovered bitumen-rich fraction; and (iv) a hydrogen sulphide concentration of gaseous material derived from the gaseous recovered solvent-rich fraction.

15. The method as claimed in claim 14;
wherein:
the solvent material includes paraffinic solvent.

16. The method as claimed in claim 14 or 15;
wherein:
the at least one process parameter includes at least one of:
a bitumen ore type parameter representative of a type of the bitumen ore;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the bitumen ore;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the multi-phase bituminous admixture;

a froth volume parameter representative of a rate of flow of the bitumen-rich froth overflow;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the gaseous deaeration operation output material;
a fractionatable bitumen-rich separation fraction flowrate representative of a rate of flow of the fractionatable bitumen-rich separation fraction;
a fractionation temperature parameter representative of a temperature at which the fractionatable bitumen-rich separation fraction is being fractionated;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the liquid bitumen-rich product material;
a liquid bitumen-rich product material flowrate representative of a rate of flow of the liquid bitumen-rich product material;
a temperature parameter representative of the temperature of the liquid bitumen-rich product material;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of gaseous material derived from the gaseous solvent-rich output material; and a solvent recovery flowrate parameter representative of a rate of flow of the gaseous solvent-rich output material.

17. The method as claimed in any one of claims 14 to 16;
wherein:
the bitumen ore is derived from a surge pile; and the at least one process parameter includes a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of a gaseous environment disposed in mass transfer communication with the surge pile.

18. The method as claimed in any one of claims 14 to 17;
wherein:
the modifying of the original process configuration includes at least one of:
modulating supply of a bitumen ore, having a bitumen ore type indicated by the bitumen ore type parameter, into the process configuration;
modulating the rate of flow of the bitumen-rich separation fraction into the solvent recovery unit;
and modulating the temperature at which the fractionatable bitumen-rich separation fraction is being fractionated

19. The method as claimed in any one of claims 12 to 18;
wherein:
the modifying of the original process configuration includes modulating supply of a scavenger into the process configuration.

20. The method as claimed in any one of claims 12 to 19;
wherein:
the modifying of the original process configuration includes modulating pH of the original processed material.

21. The method as claimed in claim 20;
wherein:
the modulating includes modulating supply of an amine material to the process configuration.

22. The method as claimed in any one of claims 12 to 21;
further comprising:
processing the bitumen-comprising material via the modified process configuration.

23. A method for training a prediction machine learning model, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;
wherein:
the process parameter information includes at least one process parameter value;
each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
obtaining a hydrogen sulphide concentration measure, wherein the obtained hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material;
providing the process parameter information as an input to the prediction machine learning model, thereby generating a predicted hydrogen sulphide concentration measure as the output of the prediction machine learning model;
processing the predicted hydrogen sulphide concentration measure and the obtained hydrogen sulphide concentration measure to generate a loss;
and adjusting a plurality of learnable parameters of the prediction machine learning model based on the loss.

24. The method as claimed in claim 23;
wherein:
adjusting the plurality of learnable parameters of the prediction machine learning model based on the loss comprises using back-propagation to propagate the loss backward through the prediction machine learning model.

25. The method as claimed in claim 23 or 24, wherein:
the prediction machine learning model comprises a multi-layer perceptron neural network.

26. The method as claimed in any one of claims 23 to 25, further comprising:
repeating, one or more times, the steps of processing the bitumen-comprising material, obtaining the process parameter information, obtaining the hydrogen sulphide concentration measure, providing the process parameter information as input to the prediction machine learning model, generating the loss, and adjusting the learnable parameters, such that a trained prediction machine learning model is obtained.

27. The method as claimed in claim 26, further comprising, after obtaining the trained prediction machine learning model:
while processing the bitumen-comprising material, using the trained prediction machine learning model to generate the predicted hydrogen sulphide concentration measure.

28. The method as claimed in claim 26 or 27, further comprising:

presenting, to an operator of the process configuration, via an output device, the predicted hydrogen sulphide concentration measure generated by the trained prediction machine learning model.

29. A method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
while supplying one or more material inputs to an original process configuration, wherein at least one of the one or more material inputs is the bitumen-comprising material, such that the bitumen-comprising material is processed via the original process configuration with effect that one or more derivative materials, derived from the one or more material inputs, are established, wherein the one or more derivative materials include one or more product material outputs, wherein each one of the one or more product material outputs, independently, is discharged from the process configuration, and at least one, of the one or more product material outputs, includes bitumen:
obtaining process parameter information;
wherein:
the process parameter information includes at least one process parameter value;

each one of the at least one process parameter value, independently, is representative of a value of a respective process parameter, such that at least one process parameter is provided; and each one of the at least one process parameter, independently, is representative of a parameter of the processing of the bitumen-comprising material via the original process configuration;
and processing the process parameter information, using a trained prediction machine learning model, to predict a hydrogen sulphide concentration measure of a processed material, defined by one of the one or more derivative materials, wherein the hydrogen sulphide concentration measure is representative of a concentration of hydrogen sulphide of the processed material.

30. The method as claimed in claim 29;
wherein:
the hydrogen sulphide concentration measure is a concentration of hydrogen sulphide of the processed material.

31. The method as claimed in claim 30;
wherein:
the processing via the original process configuration includes:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth overflow intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth overflow is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least a solvent-conditioned bitumen-rich separation fraction and a solids-rich separation fraction; and within a solvent recovery unit, fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility;
and the hydrogen sulphide concentration measure includes at least one of:
(v) a hydrogen sulphide concentration of the liquid recovered bitumen-rich fraction; and (vi) a hydrogen sulphide concentration of gaseous material derived from the gaseous recovered solvent-rich fraction.

32. The method as claimed in claim 31;
wherein:
the solvent material includes paraffinic solvent.

33. The method as claimed in claim 31 or 32;
wherein:
the at least one process parameter includes at least one of:
a bitumen ore type parameter representative of a type of the bitumen ore;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the bitumen ore;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the multi-phase bituminous admixture;
a froth volume parameter representative of a rate of flow of the bitumen-rich froth overflow;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the gaseous deaeration operation output material;
a fractionatable bitumen-rich separation fraction flowrate representative of a rate of flow of the fractionatable bitumen-rich separation fraction;

a fractionation temperature parameter representative of a temperature at which the fractionatable bitumen-rich separation fraction is being fractionated;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of the liquid bitumen-rich product material;
a liquid bitumen-rich product material flowrate representative of a rate of flow of the liquid bitumen-rich product material;
a temperature parameter representative of the temperature of the liquid bitumen-rich product material;
a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of gaseous material derived from the gaseous solvent-rich output material; and a solvent recovery flowrate parameter representative of a rate of flow of the gaseous solvent-rich output material.

34. The method as claimed in any one of claims 31 to 33;
wherein:
the bitumen ore is derived from a surge pile; and the at least one process parameter includes a hydrogen sulphide concentration parameter representative of a concentration of hydrogen sulphide of a gaseous environment disposed in mass transfer communication with the surge pile.

35. A method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth inermediate is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;

via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least fractionatable bitumen-rich separation fraction and a solids-rich separation fraction; and fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility;
wherein:
the liquid recovered bitumen-rich fraction includes:
at least 99 weight % bitumen, based on the total weight of the liquid recovered bitumen-rich fraction; and mercaptan material defined by at least one mercaptan compound, each one of the at least one mercaptan compound, independently, is of formula (I):
R-S-H
wherein R is an organic group;
and the liquid recovered bitumen-rich fraction is disposed at a temperature of less than 130 degrees Celsius.

36. A method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth inermediate is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least fractionatable bitumen-rich separation fraction and a solids-rich separation fraction;
fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility; and conducting a bitumen-rich product material, derived from the liquid recovered bitumen-rich fraction, to a storage tank, such that the bitumen-rich product material becomes emplaced within the storage tank, such that stored bitumen-rich product material is established within the storage tank;
wherein:
the liquid recovered bitumen-rich fraction includes:
at least 99 weight % bitumen, based on the total weight of the liquid recovered bitumen-rich fraction; and mercaptan material defined by at least one mercaptan compound, each one of the at least one mercaptan compound, independently, is of formula (I):
R-S-H
wherein R is an organic group;

wherein:
the content of the mercaptan material within the liquid recovered bitumen-rich fraction is a H2S-generation effective mercaptan content; and an equivalent mercaptan content, to the H2S-generation effective mercaptan content, within the stored bitumen product material, is effective, at a temperature of at least 130 degrees Celsius, for effecting establishment of an H2S concentration of greater than 2 ppm within the stored bitumen output material;
and the liquid recovered bitumen-rich fraction is disposed at a temperature of less than 130 degrees Celsius.

37. A
method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a separable multi-phase bituminous material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth intermediate, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth inermediate is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a conditionable bitumen-rich intermediate, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least fractionatable bitumen-rich separation fraction and a solids-rich separation fraction;
fractionating a fractionatable bitumen-rich separation fraction, that is derived from the bitumen-rich separation fraction, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility;
modulating a temperature representative of the temperature of the liquid recovered bitumen-rich fraction, based upon the concentration of H2S within the liquid recovered bitumen-rich fraction.

38. A
method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a multi-phase bituminous feed material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth overflow feed, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth overflow is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a bitumen-rich intermediate feed, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least a solvent-conditioned bitumen-rich separation fraction and a solids-rich separation fraction;

fractionating a bitumen-rich separation fraction feed, that is derived from the bitumen-rich separation fraction, via a solvent recovery unit, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility; and conducting a bitumen-rich product material, derived from the liquid recovered bitumen-rich fraction, to a storage tank, such that the bitumen-rich product material becomes emplaced within the storage tank, such that stored bitumen-rich product material is established within the storage tank.
wherein:
the liquid recovered bitumen-rich fraction includes:
at least 99 weight % bitumen, based on the total weight of the liquid recovered bitumen-rich fraction; and mercaptan material defined by at least one mercaptan compound, each one of the at least one mercaptan compound, independently, is of formula (I):
R-S-H
wherein R is an organic group;
and the bitumen-rich separation fraction feed is supplied to the solvent recovery unit at a rate that is ineffective for effecting establishment of an concentration of greater than 2 ppm within the stored bitumen-rich product material.

39. A method for processing bitumen-comprising material, derived from a bitumen ore, comprising:
admixing a bituminous material, water, and air, such that a multi-phase bituminous admixture is produced, the bituminous material being material that is derived from the bitumen ore;
via froth flotation, separating a multi-phase bituminous feed material, that is derived from the multi-phase bituminous admixture, into at least a bitumen-rich froth overflow and a bitumen-lean underflow;
deaerating a bitumen-rich froth overflow feed, that is derived from the bitumen-rich froth overflow, with effect that the bitumen-rich froth overflow is separated into at least a deaerated bitumen-rich intermediate and a gaseous de-aeration operation output material;
admixing a bitumen-rich intermediate feed, derived from the deaerated bitumen-rich intermediate, with a solvent material, with effect that a conditioned bitumen-rich intermediate is produced;
via gravity separation, separating a separable conditioned bitumen-rich intermediate, that is derived from the solvent-conditioned bitumen-rich intermediate, into at least a solvent-conditioned bitumen-rich separation fraction and a solids-rich separation fraction; and fractionating a bitumen-rich separation fraction feed, that is derived from the bitumen-rich separation fraction, via a solvent recovery unit, into at least a liquid recovered bitumen-rich fraction and a gaseous recovered solvent-rich fraction, based on relative volatility;
modulating a rate of flow, representative of the rate of flow of the bitumen-rich separation fraction feed being supplied to the solvent recovery unit, based upon at least one of:
the concentration of H2S within the liquid recovered bitumen-rich fraction; and the concentration of H2S within gaseous material derived from the gaseous recovered solvent-rich fraction.