US20220374913A1

US20220374913A1 - Measuring of carbon footprint in offshore drilling

Info

Publication number: US20220374913A1
Application number: US17/664,123
Authority: US
Inventors: Marcos Allen
Original assignee: Schlumberger Technology Corp
Current assignee: Schlumberger Technology Corp
Priority date: 2021-05-19
Filing date: 2022-05-19
Publication date: 2022-11-24
Also published as: WO2022246083A1; US20220372860A1; CA3219619A1; CA3219052A1; EP4341888A1; EP4341529A1; WO2022246082A1

Abstract

Methods, computing systems, and computer-readable media are provided. A carbon footprint baseline is established for a drilling unit. Power consumption is calculated for drilling unit components. The power consumption of components is converted to CO2 emissions according to a GHG standard. The power consumption is transformed into real-time power consumption during drilling operations using power ratings, diversity factors, fuel usage, and specific fuel oil consumption. Real-time CO2 emissions are calculated based on the real-time power consumption. CO2 emissions calculations and modelling of supply transport units are performed based on previously collected power consumption data from supply transport units. The real-time CO2 emissions for the drilling operations are determined and presented.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No. 63/201,931, filed on 19 May 2021, U.S. Provisional Application No. 63/203,000 filed on 2 Jul. 2021, and U.S. Provisional Application No. 63/280,912, filed on 18 Nov. 2021. Each of the foregoing applications is incorporated by reference.

BACKGROUND

A commitment of net zero carbon emissions by 2050 aligns with climate science to limit temperature rise by 1.5 deg C. pre-industrial levels. While low carbon energy sources will significantly reduce scope 1 emissions, a transition will take time to introduce.
With drilling activities predicted to increase over a next 15 to 20 years, decarbonizing drilling activities remains a focal point of major stakeholders.
A standard approach used in the oil, gas and energy industry is top-down calculations with generic fuel consumption and conversions to greenhouse gas (GHG) emissions. Top-down calculations of carbon emissions are not a most effective measure of a carbon footprint of greenhouse gasses. An aim of the top-down approach is to detect emissions associated with an apparent consumption of primary fuels associated with drilling of an oil well.

SUMMARY

Embodiments of the disclosure may provide a method for monitoring real-time CO₂emissions for a drilling operation. According to the method, a carbon footprint baseline is established, by a computing device, for a drilling unit. The establishing includes calculating power consumption, including power supply and power demand, for components of the drilling unit based on previously collected data representing the components of the drilling unit. The power consumption of the components of the drilling unit are converted to CO₂emissions according to a greenhouse gas (GHG) standard. The calculated power consumption is transformed into real-time power consumption during drilling operations using power ratings, diversity factors, fuel usage, and specific fuel oil consumption based on the previously collected data. Real-time CO₂emissions are calculated during the drilling operations based on the real-time power consumption. CO₂emissions calculations and modelling of supply transport units are performed based on previously collected power consumption data from supply transport units of a same type as the modelled supply transport units during support of previous drilling operations. The real-time CO₂emissions for the drilling operations are determined and presented.
In an embodiment, the method may include determining whether to approve a revised drilling plan based on the calculated CO₂emissions and predicted reduced CO₂emissions based on using CO₂emission mitigating technology
In an embodiment, the method may include analyzing the carbon footprint baseline to determine largest sources of CO₂emissions. A revised drilling plan focused on reducing the CO₂emissions from the largest sources of CO₂emissions is developed. The carbon footprint baseline is updated based on the revised drilling plan. The reduced CO₂emissions are predicted based on the updated carbon footprint baseline.
In an embodiment, the method may include determining a baseline CO₂emissions model for the supply transport units to support drilling operations of the drilling unit based on previously collected data regarding multiple representative supply transport units supporting previous drilling operations. The previously collected data regarding the multiple representative supply transport units includes collected data on fuel consumptions, speeds, positions, and operational modes.
In an embodiment, the method may include receiving helicopter flight data used for support of a drilling unit to drill well sections. CO₂emissions are calculated per helicopter flight based on the received helicopter flight data.
In an embodiment, the method may include converting the calculated power demand to real power demand on an equipment level using previously collected real-time data for corrected power rating. Based on the real power demand, the CO₂emissions are calculated to provide the carbon footprint baseline for the mobile offshore drilling unit.
In an embodiment, the method may include a GHG Corporate Accounting and Reporting Standard.
Embodiments of the disclosure may also provide a computing system. The computing system includes at least one processor and a memory connected with the at least one processor. The memory includes instructions for the at least one processor to perform operations. According to the operations, a carbon footprint baseline for a drilling unit is established. Establishing the carbon footprint baseline includes calculating power consumption, including power supply and power demand, for components of the drilling unit based on previously collected data representing the components of the drilling unit. The power consumption of the components of the drilling unit is converted to CO₂emissions according to a greenhouse gas (GHG) standard. The calculated power consumption is transformed into real-time power consumption during drilling operations using power ratings, diversity factors, fuel usage, and specific fuel oil consumption based on the previously collected data. Real-time CO₂emissions during the drilling operations are calculated based on the real-time power consumption. CO₂emissions calculations and modelling of supply transport units are performed based on previously collected power consumption data from supply transport units of a same type as the modelled supply transport units during support of previous drilling operations. The real-time CO₂emissions for the drilling operations are determined and presented.
Embodiments of the disclosure may further provide a non-transitory computer-readable medium having recorded thereon instructions for at least one processor to perform operations. According to the operations, a carbon footprint baseline for drilling unit is established. The baseline is established by calculating power consumption, including power supply and power demand, for components of the drilling unit based on previously collected data regarding the components of the drilling unit. The power consumption of the components of the drilling unit is converted to CO₂emissions according to a greenhouse gas (GHG) standard. The calculated power consumption is transformed into real-time power consumption during drilling operations using power ratings, diversity factors, fuel usage, and specific fuel oil consumption based on the previously collected data during drilling operations. Real-time CO₂emissions are calculated during drilling operations based on the real-time power consumption. CO₂emissions calculations and modelling of supply transport units are performed based on previously collected power consumption data from supply transport units of a same type as the modelled supply transport units during support of previous drilling operations. CO₂emissions for the drilling operations are determined and presented.
It will be appreciated that this summary is intended merely to introduce some aspects of the present methods, systems, and media, which are more fully described and/or claimed below. Accordingly, this summary is not intended to be limiting.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present teachings and together with the description, serve to explain the principles of the present teachings. In the figures:

FIG. 1 illustrates an example of a system that includes various management components to manage various aspects of a geologic environment, according to an embodiment.

FIG. 2 illustrates definitions of terms used with respect to a load analysis.

FIG. 3 illustrates multiple ways of calculating CO₂emissions.

FIG. 4 shows an example drilling platform load analysis.

FIG. 5 illustrates calculated specific fuel oil consumption and power ratings of mobile offshore drilling units according to an embodiment.

FIG. 6 illustrates a time versus depth graph for a typical production well.

FIG. 7 illustrates engine configurations of sample offshore supply vessels.

FIG. 8 shows sample recorded data for an offshore supply vessel.

FIG. 9 shows CO₂emissions per helicopter round trip.

FIG. 10 shows a sample flight manifest regarding outbound helicopter flights.

FIG. 11 shows model methodology according to an embodiment.

FIG. 12 shows 24-month post operations fuel consumption data.

FIG. 13 shows a granular analysis of a platform drilling typical well sections.

FIG. 14 shows a granular analysis of a drillship drilling typical well sections.

FIG. 15 shows granular analysis of a semisubmersible drilling typical well sections.

FIG. 16 illustrates CO₂emissions calculations for a typical drilling platform.

FIG. 17 shows a basic well planning tool used to drill a 17½ inch well section from a well-plan drilling platform according to an embodiment.

FIG. 18 shows platform CO2 emissions to drill typical well-sections.

FIG. 19 shows drillship CO2 emissions to drill typical well-sections.

FIG. 20 shows semisubmersible CO2 emissions to drill typical well-sections.

FIG. 21 illustrates operational modes for offshore supply vessels during drilling operation support.

FIG. 22 shows a dataset for an offshore supply vessel for CO₂emissions.

FIG. 23 shows percentage of total CO₂emissions for an offshore supply vessel supporting a drillship, a semisubmersible, and a platform according to an embodiment.

FIG. 24 illustrates percentage of CO₂emission per offshore supply vessel and different operational modes.

FIG. 25 shows a time versus depth drilling chart for a drilling platform along with CO₂emissions for an offshore supply vessel.

FIG. 26 shows CO₂emissions related to a drillship according to an embodiment.

FIG. 27 shows helicopter data analysis added to a depth versus time drill planning chart for drilling production well sections.

FIG. 28 illustrates a number of helicopter flights and a number of passengers predicted to support drilling of a production well.

FIG. 29 is a flowchart that illustrates an example process for determining a carbon footprint baseline related to a mobile offshore drilling unit.

FIG. 30 is a flowchart that shows an example process for updating a carbon footprint baseline based on a revised drilling plan and predicting CO₂emissions based on the updated carbon footprint baseline.

FIG. 31 illustrates a schematic view of a computing system, according to an embodiment.

DETAILED DESCRIPTION

Reference will now be made in detail to embodiments, examples of which are illustrated in accompanying drawings and figures. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to one of ordinary skill in the art that the invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.
It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first object or step could be termed a second object or step, and, similarly, a second object or step could be termed a first object or step, without departing from the scope of the present disclosure. The first object or step, and the second object or step, are both, objects or steps, respectively, but they are not to be considered the same object or step.
The terminology used in the description herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used in this description and the appended claims, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Further, as used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context.
Attention is now directed to processing procedures, methods, techniques, and workflows that are in accordance with some embodiments. Some operations in the processing procedures, methods, techniques, and workflows disclosed herein may be combined and/or the order of some operations may be changed.
FIG. 1 illustrates an example of a system 100 that includes various management components 110 to manage various aspects of a geologic environment 150 (e.g., an environment that includes a sedimentary basin, a reservoir 151, one or more faults 153-1, one or more geobodies 153-2, etc.). For example, the management components 110 may allow for direct or indirect management of sensing, drilling, injecting, extracting, etc., with respect to the geologic environment 150. In turn, further information about the geologic environment 150 may become available as feedback 160 (e.g., optionally as input to one or more of the management components 110).
In an example of FIG. 1, the management components 110 include a seismic data component 112, an additional information component 114 (e.g., well/logging data), a processing component 116, a simulation component 120, an attribute component 130, an analysis/visualization component 142 and a workflow component 144. In operation, seismic data and other information provided per the components 112 and 114 may be input to the simulation component 120.
In an example embodiment, the simulation component 120 may rely on entities 122. Entities 122 may include earth entities or geological objects such as wells, surfaces, bodies, reservoirs, etc. In the system 100, the entities 122 can include virtual representations of actual physical entities that are reconstructed for purposes of simulation. The entities 122 may include entities based on data acquired via sensing, observation, etc. (e.g., the seismic data 112 and other information 114). An entity may be characterized by one or more properties (e.g., a geometrical pillar grid entity of an earth model may be characterized by a porosity property). Such properties may represent one or more measurements (e.g., acquired data), calculations, etc.
In an example embodiment, the simulation component 120 may operate in conjunction with a software framework such as an object-based framework. In such a framework, entities may include entities based on pre-defined classes to facilitate modeling and simulation. A commercially available example of an object-based framework is the MICROSOFT® .NET® framework (Redmond, Wash.), which provides a set of extensible object classes. In the .NET® framework, an object class encapsulates a module of reusable code and associated data structures. Object classes can be used to instantiate object instances for use in by a program, script, etc. For example, borehole classes may define objects for representing boreholes based on well data.
In the example of FIG. 1, the simulation component 120 may process information to conform to one or more attributes specified by the attribute component 130, which may include a library of attributes. Such processing may occur prior to input to the simulation component 120 (e.g., consider the processing component 116). As an example, the simulation component 120 may perform operations on input information based on one or more attributes specified by the attribute component 130. In an example embodiment, the simulation component 120 may construct one or more models of the geologic environment 150, which may be relied on to simulate behavior of the geologic environment 150 (e.g., responsive to one or more acts, whether natural or artificial). In the example of FIG. 1, the analysis/visualization component 142 may allow for interaction with a model or model-based results (e.g., simulation results, etc.). As an example, output from the simulation component 120 may be input to one or more other workflows, as indicated by a workflow component 144.
As an example, the simulation component 120 may include one or more features of a simulator such as the ECLIPSE™ reservoir simulator (Schlumberger Limited, Houston Tex.), the INTERSECT™ reservoir simulator (Schlumberger Limited, Houston Tex.), etc. As an example, a simulation component, a simulator, etc. may include features to implement one or more meshless techniques (e.g., to solve one or more equations, etc.). As an example, a reservoir or reservoirs may be simulated with respect to one or more enhanced recovery techniques (e.g., consider a thermal process such as SAGD, etc.).
In an example embodiment, the management components 110 may include features of a commercially available framework such as the PETREL® seismic to simulation software framework (Schlumberger Limited, Houston, Tex.). The PETREL® framework provides components that allow for optimization of exploration and development operations. The PETREL® framework includes seismic to simulation software components that can output information for use in increasing reservoir performance, for example, by improving asset team productivity. Through use of such a framework, various professionals (e.g., geophysicists, geologists, and reservoir engineers) can develop collaborative workflows and integrate operations to streamline processes. Such a framework may be considered an application and may be considered a data-driven application (e.g., where data is input for purposes of modeling, simulating, etc.).
In an example embodiment, various aspects of the management components 110 may include add-ons or plug-ins that operate according to specifications of a framework environment. For example, a commercially available framework environment marketed as the OCEAN® framework environment (Schlumberger Limited, Houston, Tex.) allows for integration of add-ons (or plug-ins) into a PETREL® framework workflow. The OCEAN® framework environment leverages .NET® tools (Microsoft Corporation, Redmond, Wash.) and offers stable, user-friendly interfaces for efficient development. In an example embodiment, various components may be implemented as add-ons (or plug-ins) that conform to and operate according to specifications of a framework environment (e.g., according to application programming interface (API) specifications, etc.).
FIG. 1 also shows an example of a framework 170 that includes a model simulation layer 180 along with a framework services layer 190, a framework core layer 195 and a modules layer 175. The framework 170 may include the commercially available OCEAN® framework where the model simulation layer 180 is the commercially available PETREL® model-centric software package that hosts OCEAN® framework applications. In an example embodiment, the PETREL® software may be considered a data-driven application. The PETREL® software can include a framework for model building and visualization.
As an example, a framework may include features for implementing one or more mesh generation techniques. For example, a framework may include an input component for receipt of information from interpretation of seismic data, one or more attributes based at least in part on seismic data, log data, image data, etc. Such a framework may include a mesh generation component that processes input information, optionally in conjunction with other information, to generate a mesh.
In the example of FIG. 1, the model simulation layer 180 may provide domain objects 182, act as a data source 184, provide for rendering 186 and provide for various user interfaces 188. Rendering 186 may provide a graphical environment in which applications can display their data while the user interfaces 188 may provide a common look and feel for application user interface components.
As an example, the domain objects 182 can include entity objects, property objects and optionally other objects. Entity objects may be used to geometrically represent wells, surfaces, bodies, reservoirs, etc., while property objects may be used to provide property values as well as data versions and display parameters. For example, an entity object may represent a well where a property object provides log information as well as version information and display information (e.g., to display the well as part of a model).
In the example of FIG. 1, data may be stored in one or more data sources (or data stores, generally physical data storage devices), which may be at the same or different physical sites and accessible via one or more networks. The model simulation layer 180 may be configured to model projects. As such, a particular project may be stored where stored project information may include inputs, models, results and cases. Thus, upon completion of a modeling session, a user may store a project. At a later time, the project can be accessed and restored using the model simulation layer 180, which can recreate instances of the relevant domain objects.
In the example of FIG. 1, the geologic environment 150 may include layers (e.g., stratification) that include a reservoir 151 and one or more other features such as the fault 153-1, the geobody 153-2, etc. As an example, the geologic environment 150 may be outfitted with any of a variety of sensors, detectors, actuators, etc. For example, equipment 152 may include communication circuitry to receive and to transmit information with respect to one or more networks 155. Such information may include information associated with downhole equipment 154, which may be equipment to acquire information, to assist with resource recovery, etc. Other equipment 156 may be located remote from a well site and include sensing, detecting, emitting or other circuitry. Such equipment may include storage and communication circuitry to store and to communicate data, instructions, etc. As an example, one or more satellites may be provided for purposes of communications, data acquisition, etc. For example, FIG. 1 shows a satellite in communication with the network 155 that may be configured for communications, noting that the satellite may additionally or instead include circuitry for imagery (e.g., spatial, spectral, temporal, radiometric, etc.).
FIG. 1 also shows the geologic environment 150 as optionally including equipment 157 and 158 associated with a well that includes a substantially horizontal portion that may intersect with one or more fractures 159. For example, consider a well in a shale formation that may include natural fractures, artificial fractures (e.g., hydraulic fractures) or a combination of natural and artificial fractures. As an example, a well may be drilled for a reservoir that is laterally extensive. In such an example, lateral variations in properties, stresses, etc. may exist where an assessment of such variations may assist with planning, operations, etc. to develop a laterally extensive reservoir (e.g., via fracturing, injecting, extracting, etc.). As an example, the equipment 157 and/or 158 may include components, a system, systems, etc. for fracturing, seismic sensing, analysis of seismic data, assessment of one or more fractures, etc.
As mentioned, the system 100 may be used to perform one or more workflows. A workflow may be a process that includes a number of worksteps. A workstep may operate on data, for example, to create new data, to update existing data, etc. As an example, a may operate on one or more inputs and create one or more results, for example, based on one or more algorithms. As an example, a system may include a workflow editor for creation, editing, executing, etc. of a workflow. In such an example, the workflow editor may provide for selection of one or more pre-defined worksteps, one or more customized worksteps, etc. As an example, a workflow may be a workflow implementable in the PETREL® software, for example, that operates on seismic data, seismic attribute(s), etc. As an example, a workflow may be a process implementable in the OCEAN® framework. As an example, a workflow may include one or more worksteps that access a module such as a plug-in (e.g., external executable code, etc.).
Various embodiments utilize equipment manufacturers' power ratings and consumption numbers to calculate, using a bottom-up approach, greenhouse gas (GHG) emissions for individual pieces of equipment, together with operational parameters, and duty factors. The bottom-up approach achieves more accurate results for GHG emission calculations and adds granularity to focus attention on equipment that produces most of the GHG emissions to guide GHG emission remediation efforts. Quantitative data was formulated into a drilling platform load analysis to calculate power consumption of the equipment's components. Definitions used in the load analysis were as shown in FIG. 2.
In some embodiments, three sections of a production well, 17½″, 12¼″ and 8½″ were used to quantify emissions for each drilling unit developing a bottom-up carbon footprint of each unit to compare for same operations.
Several recognized standards are available for converting power usage of all equipment to CO₂emissions. Most relevant standards include a GHG Corporate Accounting and Reporting Standard (GHG Protocol, 2015) and International Maritime Organization (IMO) standards (International Maritime Organization, 2014). The GHG Protocol guidelines provide a calculated method and a direct method. Accurate data is to be provided for the calculated method. The calculated method is used by various embodiments disclosed herein.
GHG protocol standards were used to calculate the GHG emissions and develop a carbon footprint baseline. The calculations for GHG offer a variety of choices based on available information. See FIG. 3. Other GHG emissions also include CH₄and N₂₀; these make up exhaust from combustion of fossil fuels. With CO₂being between 12-17% of exhaust gases, N₂+O₂+H₂O are approximately 82-87%. All other gases together are less than 1%. Hydrocarbons are less than 0.1% for CH₄and NO₂and CO₂e. CO₂was calculated for this model.
During a design phase of a drilling unit, power supply and demand may be considered. For example, too much power may increase expenses and thus decrease revenue, while too little power may impact the performance and efficiency of drilling operations and/or impact the safety thereof. Drilling operations refer to an entire well construction/delivery process, which may include flat time activities including, but not limited to, rih casing and cementing operations. A supply and demand analysis may be provided to drilling unit owners in a form of a “Load Analysis”. The drilling unit owners and classification societies verify the load analysis during a rig acceptance and sea trials to confirm that the drilling unit is fit for its intended purpose and safe to continue operations.
The load analysis provides a static indication of loads with predetermined operational parameters, allowing a rig builder to demonstrate operational limitations of the drilling unit. Offset data may be used to transform and analyze the load analysis into real-time drilling operations and GHG emissions, determining power rating and diversity factors. In various embodiments, this was achieved through a 24-month case study of each drilling unit, measuring the power rating, diversity factor, fuel usage and specific fuel oil consumption (SFOC). This allowed the CO₂emissions footprint model to generate average overall operations; using a probabilistic Monte Carlo type evaluation allows for a P50 estimate for confidence in drilling operations of the drilling units.
Drilling demands a constant supply of fuel, consumables, spare parts and equipment to be used to construct drilling wells that may use thousands of meters of steel pipes called casings. To meet demands of mobile offshore drilling units (MODUs), three specialized offshore supply boats may be used that have a large deck loading capacity and dynamic positioning to be able to work near the MODU. In some embodiments, the CO₂emissions calculations and modeling of offshore supply vessels (OSVs), was based on data supplied by an offshore supply vessels management company specializing in optimizing fuel and CO₂emissions for OSV owners.
To meet demands of land-based drilling units, CO₂emissions calculations and modeling of all equipment, transportation, and materials to support well construction operations may be modeled based on provided information.
To support drilling operations many specialized personnel may be involved. These personnel may work 12 hour shifts with operations continuing 24 hours a day, seven days a week, 365 days a year. Several crew change methods exist to comply with many countries' unique labor laws and company-specific working policies. For example, with respect to MODUs, in some geographic regions, where weather permits, supply boats or crew boats will carry personnel back and forth to the mobile drilling unit. When distance, weather or companies' policies do not allow for carrying personnel via boats, helicopters may provide fast and reliable crew changes.
To determine a number of crew flights over a three-month period for a typical drilling operation, offset data was used. CO₂emission calculations were performed using fuel consumption per flight. CO₂emission conversion data used the GHG protocol standards and conversion factors. The data then was correlated for a 34 day drilling parameter for drilling a typical production well section template.
Platform data for a production/drilling unit with Cameron drilling rig equipment was used. Collected drillship data was from an SHI 12000 design with dual activity, and collected semisubmersible data was from a GVA 7500 harsh environment semisubmersible with a single derrick and some offline capabilities. The CO₂emissions included services such as drilling, hotel, and dynamic positioning with the floating MODUs.
The load analysis shows rated and connected power for all equipment onboard using theoretical power factors and efficiencies of an installed generator set. See FIG. 4, which shows a drilling platform load analysis.
Operational demand data supplied by the rig builder or OEM was not considered accurate enough for real power demand because it introduced a biased opinion and inconsistency into the diversity factors (power rating) across different rig builders and OEMs. Using the 24-month case study for a fleet of MODUs, the real power rating and corrected specific fuel oil consumption of the MODUs were established (see FIG. 5) through statistical analysis of the offset data. In other embodiments, data from a case study including land-based drilling units, real power rating and corrected specific fuel oil consumption of the land-based drilling units may be established through statistical analysis of offset data.
With the P50 real power rating and corrected specific fuel oil consumption (SFOC) evaluation determined for the MODU and the land-based drilling units, a first standard drilling template may be used to compare all the different MODUs and a second standard drilling unit may be used to compare the land-based drilling units. The primary operation of a drilling uits is to drill wells. In some embodiments, 3 sections of a production well were used in the standard template; the sections included 17½″, 12¼″ and 8½″ (see FIG. 6, which is a time versus depth graph for a typical MODU production well).
Semisubmersible and drill ship dynamic positioning are other variables that significantly contribute to the CO₂emission footprint for these MODUs. The rig builder and original manufacturers derive rig capability models and plots to determine thrusters' diversity and power rating factors to hold station keeping or transit to locations. Mathematically calculated scenarios determine maximum weather conditions in specific geographic regions in which a dynamically positioned MODU can perform normal drilling operations or should cease drilling and go into survival mode to ride out the weather conditions. Such scenarios are unique to the MODU. These characteristics differ considerably between semisubmersibles and drillships. The capability plots show all the thrusters' power ratings and can be correlated to a theoretical load analysis.
For a statistical comparison, these ratings would be comparable to the maximum weather conditions to allow normal drilling operations and more comparable to a P90 percentile of load analysis. However, it was decided not to use this data in the baseline carbon footprint model for MODUs without specific capability plots for drillships or semisubmersibles. Instead, the power rating from the 24-month study (P50 power rating) would be used to extract a real power demand.
Unlike the MODU, opportunities to reduce CO₂emissions related to OSVs are not derived from equipment level initiatives, but are derived from fleet optimization. Determining power consumption to a same granular level as the more complex MODU was unnecessary, which influenced data collection. See FIG. 7, which shows engine configurations of each sample OSV.
Proving a concept of a baseline CO₂emissions model to support the MODUs, a standard template was used for comparison. A 90-day study was performed by an offshore supply vessel management company using three representative offshore supply vessels. These were typical to supporting drilling operations, collecting data on fuel consumptions, speeds, positions and operational modes based between ˜130 kms between a port and the MODU. A weighted average was then calculated for each operational mode and pro-rated over typical production well drilling times and support.
The offshore supply vessel management company collected data using specialized equipment to monitor fuel consumption, improved AIS (automatic identification system) and GPS systems tracking OSV movements and speeds to determine operating modes. The data collected demonstrated typical support functions for a mobile offshore drilling unit over 3 months. The support for these well-sections ranged from drilling tools, casing, various chemicals, and drilling muds. FIG. 8 shows recorded data for an OSV.
Regarding helicopter logistics, a study collected all flight data for a platform off the coast of Brazil for 90 days with aggregated data used for support of the MODU to drill the well sections over a 34 day time period. The platform was located 110 kms away from a local helicopter base, and each flight was one hour each way. A helicopter used to collect this data was the AgustaWestland AW139 (see FIG. 9, which shows CO₂emissions), a commonly used type for offshore support, with the specification available on the manufacturer's website.
CO₂emissions per flight were calculated using the specified GHG protocol standards. See FIG. 10, which shows a sample flight manifest.
To prove the concept of a CO₂emissions footprint for a selection of MODUs, specific templates and assumptions were made to ensure comparisons of all the MODUs were made equally. These comparisons allow an end-user an overarching picture of all scope 1 CO₂emissions; however, bespoke data would be used for further detailed CO₂emissions. These assumptions have been broken down into specifics in each significant component.
For the MODUs the following assumptions were used.

- All mobile offshore drilling units are powered by marine engines using marine diesel oil (MDO).
- There are no allowances for intelligent power management systems, “closed-bus” configurations or other power-saving initiatives.
- There are no hybrid energy sources used.
- The emissions captured are only for drilling operations; no data has been collected for transit, idle periods, stacked rigs or between-well maintenance.
- There was no data for emissions from flaring operations because these are not considered “normal” drilling during the well-sections used within this specification.
- Dual activity drillships assumed equal and full use of both main and auxiliary well centers.

All these definitions and assumptions may be more defined in a bespoke carbon footprint model. However, this specification proves the concept of carbon footprint modelling for MODUs.
One aspect of offshore drilling is support of offshore supply vessels (OSVs). This activity was shown to contribute to a considerable carbon footprint. The responsibilities of the logistical operations and management of the OSV are frequently focused primarily on operational needs and less on CO₂emissions. The assumptions made are in line with the influence the relevant stakeholders have on the OSV's.

- All offshore supply vessels are powered by marine engines using marine diesel oil (MDO); there are no allowances for intelligent power management systems or “closed-bus” configurations.
- There are no specialized OSVs used, such as anchor handling units, dive support vessels.
- There are no hybrid energy sources used.
- The emissions are only captured for drilling operations support, and no data has been collected for idle periods, stacked rigs or between-well maintenance support.

The oil and gas industry has seen a rise in a number of bespoke services specializing in OSV fleet management, focusing on fuel efficiency and CO₂emissions. These areas can add significant value in CO₂emission reductions.
With the latest downturn and economic restrictions, the use of helicopter logistics has come under scrutiny. This is due in part to cost savings and charter costs. This specification has shown that helicopter logistics has a minor proportion of CO₂emission for the drilling operations but still has significant opportunities to reduce the CO₂emissions through technology and innovation.

- The helicopter used was an AgustaWestland AW139
- The passenger load was assumed to be full, the data to account for the reduction in emissions for partial loads was not available.
- A three-month weighted average was used to calculate normal drilling operations, which was then pro-rated for the 34 days of drilling a typical well.

Due to helicopter logistics' sensitivity and a competitive nature of helicopter providers, data to derive bespoke CO₂emissions may be challenging to obtain and may require various approvals. However, this specification shows that a proportion of CO₂emissions compared to CO₂emissions of an overall drilling operation is significantly less than OSV and MODUs' CO₂emissions.
The data presented thus far show a visibility of today's drilling operations for each class of the MODUs, namely a platform, semisubmersible and drillship. This section shows calculations and analysis of each MODU and a logistical aspect of the CO₂emissions footprint allowing the granularity for making an informed decision on reducing CO₂emissions.
To accurately analyze the CO₂emissions from any MODU, real power demand is calculated. Most analytic models support post-operation designs using fuel consumed to perform operations and calculate the CO₂emissions. A following process was developed to address missing information on real power demands, efficiencies, and specific fuel oil consumption (SFOC). See FIG. 11, which shows model methodology. For a model methodology for land-based drilling units, dynamic positioning capability plots may be eliminated, and OSV support and helicopter logistic support, respectively, may be replaced with land logistics.
With the 24-month post operation study performed on a fleet of MODUs, real power demand and corrected specific fuel oil consumptions (SFOC) were calculated and correlated to P90, P50 and P10 percentiles. See FIG. 12, which shows 24-month post operations fuel consumption data. A similar post operation study for land-based drilling units may also be performed to calculate real power demand and corrected specific fuel oil consumptions (SFOC) and correlate the real power demand and SFOC to P90, P50 and P10 percentiles.
The calculated power demand was then converted to real power demand on an equipment level using real-time data for corrected power rating. With the real power demand calculated, the CO₂emissions were calculated to give the baseline CO₂emissions footprint for the drilling unit. The corrected load analysis and CO₂emissions were then compared to the 24-month post-study on CO₂emissions, with results showing good correlations proving the concept for the model showing a level of acceptable accuracy. With CO₂emissions calculated in detail specific to the equipment, a highest emission responsible for the CO₂footprint can be clearly demonstrated.
FIG. 13 shows a granular analysis of a platform drilling typical well sections.
FIG. 14 shows a granular analysis of a drillship drilling typical well sections.
FIG. 15 shows granular analysis of a semisubmersible drilling typical well sections.
The CO₂emissions for each piece of equipment onboard the MODUs were then calculated to a CO₂/hour emissions figure (see FIG. 16).
Equipment responsible for highest CO₂emissions are high-pressure mud pumps, top drive and drawworks. Using this information and the CO₂emissions per hour, the well-planning tool was used to calculate a time versus depth chart versus CO₂emissions for each section. FIG. 17 shows results of a basic well planning tool used to drill a 17½ inch well section from a well-plan drilling platform.
All the analyzed data and CO₂emissions were then added to a depth versus time drilling chart used for well planning and managing drilling operations (see FIGS. 18, 19, 20). Below, it can be seen from the secondary x-axis, the total predicted CO₂emissions to drill the production well, including the OSV and helicopter logistics.
FIG. 18 shows platform CO₂emissions to drill typical well-sections.
FIG. 19 shows drillship CO₂emissions to drill typical well-sections.
FIG. 20 shows semisubmersible CO₂emissions to drill typical well-sections.
With the individual drilling units analyzed, establishing a CO₂emissions footprint on a granular level is possible; and visualizing the CO₂emissions for drilling operations and demonstrating differences between the drilling units is possible. This allows the relevant stakeholders to focus and leverage technologies to reduce CO₂emissions in relevant areas.
Using the model developed within this specification has allowed a focus on emission reduction initiatives. These emission reduction initiatives include modifying energy sources, modifying drilling equipment, or improvements to operational efficiencies.
Hybrid offshore drilling units are now proven concepts and are acceptable options for conversions and future newly built rigs; cost and carbon emission benefits range between 11% CO₂reductions and a further reduction of 33% during engine running hours. These current technologies are now available and include hybrid power plants and energy storage. These include Lithium-Ion battery technology, spinning reserve, peak shaving, and intelligent power management, allowing more efficient control over a busbar configuration.
Other technologies specific to drilling improvements or operational decisions may be divided into downhole and topside. The downhole decisions are relevant to well-designs, use of bottom hole assemblies, differentiation of drilling fluids, efficiencies of setting casing pipe, wiper trips, efficient removal of cuttings or casing while drilling, and eliminating additional hole trips out and back into the hole. The topside decisions follow similar trends and improve efficiencies on all surface equipment. Topside initiatives range from condition-based maintenance, hybrid energy sources, intelligent power management and load shaving (removing peaks and lulls in power demand), critical personnel training to ensure more consistency with less wastage in drilling time, smart drilling equipment allowing low power modes when the demand is not required. Energy source replacement includes electrification from renewable supplies or replacing diesel power generation with fuel cells consuming green hydrogen or ammonia.
It was noted that accuracy of dynamic positioning was weather dependent. In comparison to the 24-month case study for a fleet of MODUs, the accuracy decreased without the use of capability plots or station-keeping data.
To analyze the offshore supply vessels data, it was divided into several operational modes (see FIG. 21, which shows operational modes for OSVs during drilling operation support) and calculated CO₂emissions per day per vessel (see FIG. 22, which shows the dataset for an OSV for CO₂emissions). The data was then pro-rated to suit the time required to support the drilling operations for the well having sections of 17½″, 12¼″ and 8½″. This data was then converted from International Maritime Organization (IMO) standards (International maritime organization, 2014, p.58) to GHG Protocol Standards for direct emissions from stationary combustion to allow a common standard in the total emissions footprint.
Further analysis of the OSV CO₂emissions indicated that it accounted for 44% of the total CO₂emissions for a platform, 20% for a semisubmersible, and 17% for a drillship to perform drilling of the standard production well sections (see FIG. 23). With a granular level analysis per OSV and different operational modes (see FIG. 24), opportunities are available to reduce emissions without decreasing efficiency supporting drilling operations.
With the same concept to display the CO₂emissions for the drilling operations, a time versus depth drilling chart is shown in drilling unit sections (see FIG. 25). It was predicted that the CO₂emissions for logistical support of three offshore supply boats to drill the same production well sections would be 1019 metric tons CO₂.
With the offshore supply vessel logistics being a highest singular CO₂emissions (see FIG. 26) for scope 1 drilling operations, reducing CO₂emissions regarding OSV logistics may provide a most significant CO₂emissions reduction benefit. Working closely with OSV management companies and stakeholders, proven reduction technologies are available within the marketplace to achieve significant savings in CO₂emissions.
Using sophisticated throttle optimization systems, engine use analysis and bespoke mathematical algorithms to control offshore vessels together with accurate global positioning systems, specialized OSV management companies can optimize logistics and fuel consumption possibilities to produce significant savings. Case studies indicate significant fuel savings for an OSV for 12 months, the total financial savings being $373,746, which translates to 574 m3 of marine gas oil (MGO) and 1800 metric tons of CO₂(using GHG Protocol Standards) per year.
With respect to helicopter logistics, analyzing data from a 90-day flight manifest and pro-rating total CO₂emissions for a 34 day period for drilling the typical well sections was 110 metric tons of CO₂. The analytics demonstrated that helicopter logistics accounts for significantly less CO₂emissions than drilling and OSVs. With CO₂emissions less than 5% for a drilling platform, 2% for the drillship and 2.1% for the semisubmersible.
The helicopter data analysis was then added to a depth versus time drill planning chart to drill the production well-sections by a drilling platform described earlier (see FIG. 27). Total CO₂emissions calculated for helicopter logistics were 110 metric tons.
Using a helicopter manifest analysis and assumed cost of $5000/hr charter, the helicopter charter's potential costs to support the drilling platform during the same production well sections are estimated to be $360,000 (see FIG. 28, which shows a number of flights and passengers with respect to drilling the production well).
FIG. 29 shows an example flowchart describing a process for determining a carbon footprint baseline related to a MODU. The same method may be applied to components of a land-based drilling unit to determine a carbon footprint related to the land-based drilling unit. The process may begin by calculating power consumption for components of the MODU based on previously collected data regarding the components of the MODU (act 2902). The power consumption of the components of the MODU may be converted to CO₂emissions according to a GHG standard (act 2904). The calculated power consumption then may be transformed into real-time power consumption during drilling operations using power ratings, diversity factors, fuel usage, and specific fuel oil consumption based on data previously collected during drilling operations of a same type of drilling platform as the MODU (act 2906). Real-time CO₂emissions during the drilling operations may be calculated based on the real-time power consumption (act 2908). CO₂emissions calculations and modeling of offshore supply vessels may be performed based on previously collected power consumption data from offshore supply vessels of a same type as the model offshore supply vessels during support of previous drilling operations (act 2910). Offset data may be used to calculate CO₂emissions based on fuel consumption per helicopter flight and CO2 emissions conversion data (act 2912). In some embodiments, the fuel consumption per helicopter flight may be based on received helicopter flight data for a helicopter providing support of a MODU to drill well sections. A carbon footprint baseline may be used to calculate CO₂emissions for a drilling plan (act 2914). In some embodiments, the carbon footprint baseline may be calculated by converting the calculated power demand to real power demand on an equipment level using previously collected real-time data for corrected power rating, and calculating, based on the real power demand, the CO₂emissions to provide a baseline carbon footprint. Areas on which to focus may be determined and presented for reducing the carbon footprint baseline (2916).
In some embodiments, real-time carbon emissions reduction insights may be provided. For example, the drilling rate of penetration may be optimized by using parameters that limit power input of rig equipment (mud pumps, drawworks, top drive) to reduce overall carbon emissions. This can be compared to driving a car in ECO mode where a driver limits the car's performance in order to prioritize lower fuel consumption and therefore, lower carbon emissions.
FIG. 30 shows a flowchart of an example process for updating a carbon footprint baseline based on a revised drilling plan for reducing emissions, and predicting reduced CO₂emissions based on the updated carbon footprint baseline. The process may begin by analyzing the carbon footprint baseline to determine largest sources of CO₂emissions (act 3002). Next, a revised drilling plan may be developed focused on reducing CO₂emissions from the largest sources of CO₂emissions (act 3004). The carbon footprint baseline then may be updated based on the revised drilling plan (3006). Next, reduced CO₂emissions may be predicted based on the updated carbon footprint baseline (act 3008). In some embodiments, the revised drilling plan may be approved if the CO2 emissions are reduced by at least a threshold percentage such as, for example, 25% or another suitable percentage.
In some embodiments, the methods of the present disclosure may be executed by a computing system. FIG. 31 illustrates an example of such a computing system 3100, in accordance with some embodiments. The computing system 3100 may include a computer or computer system 3101A, which may be an individual computer system 3101A or an arrangement of distributed computer systems. The computer system 3101A includes one or more analysis modules 3102 that are configured to perform various tasks according to some embodiments, such as one or more methods disclosed herein. To perform these various tasks, the analysis module 3102 executes independently, or in coordination with, one or more processors 3104, which is (or are) connected to one or more storage media 3106. The processor(s) 3104 is (or are) also connected to a network interface 3107 to allow the computer system 3101A to communicate over a data network 3109 with one or more additional computer systems and/or computing systems, such as 3101B, 3101C, and/or 3101D (note that computer systems 3101B, 3101C and/or 3101D may or may not share the same architecture as computer system 3101A, and may be located in different physical locations, e.g., computer systems 3101A and 3101B may be located in a processing facility, while in communication with one or more computer systems such as 3101C and/or 3101D that are located in one or more data centers, and/or located in varying countries on different continents).
A processor may include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.
The storage media 3106 may be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of FIG. 31 storage media 3106 is depicted as within computer system 3101A, in some embodiments, storage media 3106 may be distributed within and/or across multiple internal and/or external enclosures of computing system 3101A and/or additional computing systems. Storage media 3106 may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories, magnetic disks such as fixed, floppy and removable disks, other magnetic media including tape, optical media such as compact disks (CDs) or digital video disks (DVDs), BLURAY® disks, or other types of optical storage, or other types of storage devices. Note that the instructions discussed above may be provided on one computer-readable or machine-readable storage medium, or may be provided on multiple computer-readable or machine-readable storage media distributed in a large system having possibly plural nodes. Such computer-readable or machine-readable storage medium or media is (are) considered to be part of an article (or article of manufacture). An article or article of manufacture may refer to any manufactured single component or multiple components. The storage medium or media may be located either in the machine running the machine-readable instructions, or located at a remote site from which machine-readable instructions may be downloaded over a network for execution.
In some embodiments, computing system 3100 contains one or more load analysis module(s) 3108. In the example of computing system 3100, computer system 3101A includes the load analysis module 3108. In some embodiments, a single load analysis module may be used to perform some aspects of one or more embodiments of the methods disclosed herein. In other embodiments, a plurality of load analysis modules 3108 may be used to perform some aspects of methods herein.
It should be appreciated that computing system 3100 is merely one example of a computing system, and that computing system 3100 may have more or fewer components than shown, may combine additional components not depicted in the example embodiment of FIG. 31, and/or computing system 3100 may have a different configuration or arrangement of the components depicted in FIG. 31. The various components shown in FIG. 31 may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application specific integrated circuits.
Further, the steps in the processing methods described herein may be implemented by running one or more functional modules in information processing apparatus such as general purpose processors or application specific chips, such as ASICs, FPGAs, PLDs, or other appropriate devices. These modules, combinations of these modules, and/or their combination with general hardware are included within the scope of the present disclosure.
Computational interpretations, models, and/or other interpretation aids may be refined in an iterative fashion; this concept is applicable to the methods discussed herein. This may include use of feedback loops executed on an algorithmic basis, such as at a computing device (e.g., computing system 3100, FIG. 31), and/or through manual control by a user who may make determinations regarding whether a given step, action, template, model, or set of curves has become sufficiently accurate for the evaluation of the subsurface three-dimensional geologic formation under consideration.
Over the last ten years, several models have defined predictive modelling to establish a baseline carbon footprint for planning of drilling campaigns and selection of rigs for oil companies, all of which had a same conclusion. With limited offset data available, all the models' accuracy relied on estimates and assumptions and required post operations verification.
Due to the absence of detailed and granular CO₂emissions data, it was observed that it was challenging to quantify areas of importance without establishing baseline CO₂emissions. The disclosed model also highlights roles and emissions of offshore supply vessels and helicopter emissions for drilling operations. Product verification will play a significant role in a future of CO₂emission reductions. Creditable baselines should be established before investigating solutions to reduce existing CO2 emissions. With predictive baseline modelling and predictive analysis, products can be tested before committing to possible high costs upfront.
To maximize a carbon footprint modelling effect, data should be accessible on all drilling industry levels, ranging from executive levels in crucial decision-making positions to drillers required to make decisions during critical operations while drilling. To allow options for the drilling industry, visuals should be simple for use with granularity. All data collected has been developed into an interactive dashboard giving a user options to filter and slice details of importance while still offering high-level details to compare all the different drilling units on equal templates.
The foregoing embodiments have been described with respect to drilling operations. However, the methodology used in the abovementioned embodiments may be extended in other embodiments to include, but not be limited to, workover operations and plug and abandonment (P&A) operations.
Although the abovementioned embodiments are focused on reducing CO₂emissions, other embodiments may focus on reducing CO₂e emissions as well as CO₂emissions. Still yet, other embodiments may include scopes 1-3 emissions. Scope 1 includes direct emissions. Scope 2 includes indirect emissions from purchased electricity, heating, and cooling. Scope 3 includes all other indirect emissions that exist in a company's value chain, including downstream activities.
The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or limiting to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. Moreover, the order in which the elements of the methods described herein are illustrated and described may be re-arranged, and/or two or more elements may occur simultaneously. The embodiments were chosen and described in order to best explain the principles of the disclosure and its practical applications, to thereby enable others skilled in the art to best utilize the disclosed embodiments and various embodiments with various modifications as are suited to the particular use contemplated.

Claims

What is claimed is:

1. A method for monitoring real-time CO₂emissions for a drilling operation, the method comprising:

establishing, by a computing device, a carbon footprint baseline for a drilling unit, the establishing comprising:

calculating power consumption, including power supply and power demand, for components of the drilling unit based on previously collected data representing the components of the drilling unit,

converting the power consumption of the components of the drilling unit to CO₂emissions according to a greenhouse gas (GHG) standard,

transforming the calculated power consumption into real-time power consumption during drilling operations using power ratings, diversity factors, fuel usage, and specific fuel oil consumption based on the previously collected data,

calculating real-time CO₂emissions during the drilling operations based on the real-time power consumption,

performing CO₂emissions calculations and modelling of supply transport units based on previously collected power consumption data from supply transport units of a same type as the modelled supply transport units during support of previous drilling operations, and

determining and presenting the real-time CO₂emissions for the drilling operations.

2. The method of claim 1, further comprising:

determining whether to approve a revised drilling plan based on the calculated CO₂emissions and predicted reduced CO₂emissions based on using CO₂emission mitigating technology.

3. The method of claim 1, further comprising:

analyzing the carbon footprint baseline to determine largest sources of CO₂emissions;

developing a revised drilling plan focused on reducing the CO₂emissions from the largest sources of CO₂emissions;

updating the carbon footprint baseline based on the revised drilling plan; and

predicting the reduced CO₂emissions based on the updated carbon footprint baseline.

4. The method of claim 1, further comprising:

determining a baseline CO₂emissions model for the supply transport units to support drilling operations of the drilling unit based on previously collected data regarding multiple representative supply transport units supporting previous drilling operations, the previously collected data regarding the multiple representative supply transport units including collected data on fuel consumptions, speeds, positions, and operational modes.

5. The method of claim 4, further comprising:

receiving helicopter flight data used for support of a drilling unit to drill well sections; and

calculating CO₂emissions per helicopter flight based on the received helicopter flight data.

6. The method of claim 1, further comprising:

converting the calculated power demand to real power demand on an equipment level using previously collected real-time data for corrected power rating; and

calculating, based on the real power demand, the CO₂emissions to provide the carbon footprint baseline for the drilling unit.

7. The method of claim 1, wherein the GHG standard includes a GHG Corporate Accounting and Reporting Standard.

8. A computing system for monitoring real-time CO₂emissions, the computing system comprising:

at least one processor; and

a memory connected with the at least one processor, the memory including instructions for the at least one processor to perform a plurality of operations comprising:

establishing a carbon footprint baseline for a drilling unit, the establishing comprising:

9. The computing system of claim 8, wherein the plurality of operations further comprise:

10. The computing system of claim 8, wherein the plurality of operations further comprise:

updating the carbon footprint baseline based on the revised drilling plan; and

11. The computing system of claim 8, wherein the plurality of operations further comprise:

12. The computing system of claim 11, wherein the plurality of operations further comprise:

13. The computing system of claim 8, wherein the plurality of operations further comprise:

14. The computing system of claim 8, wherein the GHG standard includes a GHG Corporate Accounting and Reporting Standard.

15. A non-transitory computer-readable medium having recorded thereon a plurality of instructions for at least one processor to perform a plurality of operations comprising:

16. The non-transitory computer-readable medium of claim 15, wherein the plurality of operations further comprise:

17. The non-transitory computer-readable medium of claim 15, wherein the plurality of operations further comprise:

updating the carbon footprint baseline based on the revised drilling plan; and

18. The non-transitory computer-readable medium of claim 15, wherein the plurality of operations further comprise:

19. The non-transitory computer-readable medium of claim 15, wherein the plurality of operations further comprise:

20. The non-transitory computer-readable medium of claim 15, wherein the plurality of operations further comprise:

calculating, based on the real power demand, the CO₂emissions to provide the carbon footprint baseline for the mobile offshore drilling unit.