White Paper Prepared by Dr. Haider Sabti, Senior ICT Consultant. October 2018  |  Download PDF Version

Companies involved in oil, gas and mining recognise that wireless Systems have become an indispensable part of daily operations to maximise production, streamline operations and comply with safety regulations. However, recent advances in the Internet of Things (IoT) have promised numerous benefits that can positively influence growth and production, safety and environmental factors. Increasingly, companies are embracing IoT technologies to support strategic decision-making, gain a competitive edge and drive business benefit.

1. Introduction

IoT (Internet of Things) trends are connecting all business levels and promising transformation. Companies are embracing various technologies and platforms to implement IoT networks such as LTE-M [1], NB-IoT [2], LoRaWAN [3], Sigfox [4], Zigbee [5] etc. Generally, IoT networks consist of a number of controlled intelligent devices, typically deployed to improve the efficiency of the engineering process, enable automation and reduce the resources wastage [6]. IoT networks are considered suitable candidates for all field operations ranging from exploration to production and refining. This is due to the IoT-enabled qualities, regularly decreased fabrication cost and device size, and low deployment expense. Statistical figures show a rapid growth in the number of IoT devices and forecast (within a few years) their numbers to increase to the tune of billions [7].

In addition to the IoT rapid growth and technology advances, a growth in the IoT applications deployment has been reported. Today’s IoT applications include; industrial control and automation [8-10], sustainability [11, 12], resources and waste management [13], and health and safety [14-16]. A comprehensive analysis of IoT applications, challenges and opportunities are discussed in [17].

IoT is rapidly evolving and growing in the oil, gas and mining applications. In the operational field, detecting and reporting catastrophic failures and/or destructive events in real-time reduces production downtime. The information delivery from the end-user to the central processing unit is vital to streamlining production. Organisations are adopting integration approaches to link multiple telecommunications and control systems, such as Programmable Logic Controller (PLC) [18], Supervisory Control and Data Acquisition (SCADA) [19], Fleet Management System (FMS) [20], Fatigue Detection System (FDS) [21] etc.

2. IoT Market Analysis

In recent years, IoT has been extensively investigated, and many applications involving IoT platforms and industrial projects have been reported in the last decade [10, 20, 22]. Gartner’s 2017 hype cycle of emerging technologies forecast most IoT related applications will achieve mainstream adoption in a 2-5 years period, as shown in Fig. 1.

The architectural design of IoT is concerned with architecture styles, networking and communication, smart objects, web services and applications, business models and corresponding process, cooperative data processing, security etc.

Figure 1: Gartner’s 2017 hype cycle of emerging technologies [23]

Layer NamePurpose
Device LayerIdentify and collect the objects’ specific information from the sensor device
Network LayerSend collected data from the device layer to the information processing system
Middleware LayerPerforms information processing and ubiquitous computation and takes decisions based on the input data
Application LayerProvides global management of the application based on the information processed through Middleware
Business LayerResponsible for the management of overall IoT system

Table I: Layered Architecture of Internet of Things.

For simplicity purposes, the IoT-based services can be categorised into five layers [24], as summarised in Table I. The layered architecture has two distinct divisions with a middleware layer in between to serve the purpose of reliable communication. The top two layers contribute to data capturing while the bottom two layers are responsible for data utilisation in applications.

From the technology perspective, the IoT architecture design needs to consider mobility, scalability, latency and interoperability among heterogeneous devices. As things change location or need real-time interaction with their environment, an adaptive architecture is needed to support dynamic interactions with other devices.

IoT placement scenarios in the oil, gas and mining environment can feature more than one cluster controlled by one or several gateways. The gateways gather raw data and route specific application information to the cloud [25] or most likely cloud edge server [26]. A practical connectivity design must provide a balance among specific radio parameters (battery life, system capacity, coverage and cost), which is rather challenging.

For example, extended transmission intervals can compensate data losses but increase battery consumption and reduce the network lifetime. A study in [27], proposed a two-stage optimisation methodology to minimise deployment cost and maximise lifetime in underground mining. Capacity is another determining factor, even though the end-device data rate is small, the gateway aggregated throughput can be large and necessitate the use of high capacity and availability links. Access technologies such as PTP/PTMP Microwave [28] or 3GPP Long Term Evolution (LTE) [29] are usually used to enable backbone communications.

Low-Power Wide Area Network (LPWAN) is a broad term encompassing various implementations and protocols, both proprietary and open-source. Proprietary systems like Ultra Narrow Band (UNB) SIGFOX, LoRaWAN, and Weightless, all targeting the low-power class of IoT applications that cannot be served by either the established local wireless networks (such as WiFi or ZigBee networks) or the Cellular networks (e.g. LTE).

3GPP established standardisation (e.g. LTE-M and NBIoT) for LTE machine-type communications (MTC) was a response to the LPWAN proprietary challenge. The focus of cellular providers was to establish a new category of low-cost User Equipment (UE) on top of the existing LTE air interface [30, 31]. Giving Cellular IoT the implementation advantage using existing evolved 4G LTE networks compare to unlicensed LPWAN. An IoT technologies comparison is given in Table II.

Sigfox uses an ultra-narrowband communication channel in the order of 100s of Hz (e.g., 100, 200, 300, etc.), the uplink transmissions are triggered when data is ready without centralised scheduling and follow a client-server model. Sigfox does not support networkoriginated calls, therefore transmissions are repeated to increase the chances of a successful reception by the network.

Similar to Sigfox, LoRa supports end-devices originated calls to prolong the network life. In addition, LoRa has the ability to originate network transmission and manages the communication bandwidth for each device to maximise the overall network capacity.

TechnologySIGFOX UNBLoRaLTE-MNB-IoT
Receiver Sensitivity-147 dBm-137 dBm-132 dBm-137 dBm
Frequency BandSub-GHz ISMSub-GHz ISMLicensedLicensed
Minimum BW100 Hz, 600Hz125 kHz180 kHz3.75 kHz
Fully Bi-directionalNoYesYesYes
ModulationD-BPSKGFSKBPSK, QPSK, 16QAM, 64QAMp/2 -BPSK, p/4 – QPSK
MACUnsoltted ALOHAALOHA UnslottedSC-FDMASC-FDMA
Data rate100 b/s0.3-38.4 kb/sUp to 1000 kb/sUp to 100 kb/s
OTA UpgradeNoYesYesYes
RoamingYesYesYesYes
StandardNoLoRaWANLTE (Rel.12)LTE (Rel.13)

Table II: Comparisons of IoT Technologies [32].

In release 12, 3GPP investigated the LTE network requirements to support MTC. A physical limitation to achieve low power and a wide range is the small data size. LTE-M have been introduced to reduce the cost and power consumption, provide lower data rate, simplified hardware, and narrowband operation. To ensure backward compatibility, LTE-M utilised the existing LTE system acquisition channel and the random-access channel of 1.08 MHz. The minimum transmission bandwidth of 180 kHz is used for one Resource Block (RB), an RB is the minimum scheduling unit of legacy LTE. In release 13, a new air interface Narrow-Band IoT (NB-IoT) is established to resolve the existed issue of cellular spectrum scarcity that is facing massive IoT applications. NB-IoT enables spectral power efficiency operation with narrower operating bandwidth of 3.75 kHz compared to LTE-M system. The NB-IoT is specifically tailored to operate in either the re-farmed GSM spectrum band, the resource block within an LTE band or the guard-band of an LTE carrier. The downside of NB-IoT is the higher upfront associated system cost that is normally required for deployment.

3. Key Applications in Oil, Gas and Mining

Market demands and innovations are key enablers of IoT technology advancement. This section presents the work that has been performed in relation to this topic.

The “Coal Mining Safety and Health Regulation [33]” and “Petroleum and Gas Production and Safety Regulation [34]” issued by the State of Queensland have discussed the requirements for safety and health management systems, communications and rescue systems, tracking and monitoring systems, early detection and prevention detection systems, among other standards and procedures. All of which is based on pervasive sensing, data collection, real-time use of data and deep data post analysis, which is based on IoT. IoT technologies play a significant role in addressing the challenges stimulated in a production environment, represented by constant change and unpredictability, the complexity of supply chain, labour and assets management, unexpected downtime and streamlining of operations.

In the oil and gas exploration and production, mining, and construction environments, IoT networks can be used to enable effective communication and interaction between humans and machines in the field, identify and track workers and assets, collect and analyse critical information to enhance the safety measures and provide early warnings and alarm notifications. Fig. 2 depicts the different IoT applications in the oil, gas and mining environment.

Figure 2: IoT applications in (a) mining (b) oil and gas environment.

3A.     Automation and Fleet Management

The automotive industry includes the use of smart things to monitor and report various parameters to monitor surrounding conditions, ranging from tyre pressure to the proximity of other vehicles. In one example, IoT mesh network is used to support communications between vehicles when cellular service becomes unavailable [35]. IoT assists autonomous vehicles to avoid obstacles by using sensory devices and enable truck-to-truck communications to maintain a safe distance from each other. In 2015, RioTinto’s Pilbara mines were the first in the world to use fully automated driverless trucks in order to move iron ore, and other big producers such as BHP and Fortescue are following the vision of automated mining [36]. The Canadian Mining Magazine published a case study on the maximisation of productivity using autonomous vehicles in underground mining [8]. A breakdown of mining activities has shown that remote loading and hauling can increase active production time in mines by as much as nine hours every day by eliminating the need for shift changes of truck operators and reducing the downtime for the blasting process. Automated and self-correcting remote operations will allow to map metrics and deploy machine learning and artificial intelligence‐based models to act on events in real  time.

3B.     Identification and Tracking

IoT end-nodes enable mobile assets tracking through their geographical information [37], support fleet management [38], and traffic control [39], for the purpose of automation [40]. Information sources such as GPS [41], Cell-ID [42], RFID [43] etc. are used to track physical locations. Monitoring and tracking applications include real-time tracking of workers and equipment to increase productivity and enhance safety, alerting supervisors when assets are moving and set geo-boundaries around explosion areas to prevent accidents. In [44] a crowdsourcing geo-fencing approach is proposed to confine the wireless access within a defined physical area. In this example the IoT locationaware and access control systems are also designed to elevate any security concerns.

3C.     Operation and Services Management

IoT systems can be used to centrally or remotely control and optimise operations, and enable effective communication between the office domain and field assets. The sum of the operations improvements would result in streamlining processes across remote worksites and results in cost savings based on the efficient management of equipment, individuals, and materials. IoT wellhead monitoring system concept is presented in [22], the proposed IoT system is capable of sensing and reliably transmitting monitored data (pressure, temperature, vibration, etc.) to the control processing facility. Real-time activities provide greater visibility in the planning and coordination of operations. It enables full and transparent control over practices and include the small stages of a process, detect anomalies and support the implementation of advanced analytics. Industrial Control System (ICS), such as SCADA leverage extensively on the Human–Machine interface (HCI) so that human operators take appropriate actions to run smooth operations. IoT inherent open network protocols provide a better and reliable mechanism to manage decentralised SCADA implementations. An IoT based SCADA integrated with Fog computing to manage power distribution automation is proposed in [45].

3D.     Health and Safety

The oil, gas and mining industry is one of the highly regulated industries, as a simple error in operations could result in loss of human life. Although, significant improvements have been made in the operations, procedures and regulations resulting in reduced rates of fatalities and serious injuries. These industries, in particular mining, still unfortunately have the highest rate of fatalities compared to any industry in Australia [46]. This is due to the heavy machinery, materials involved, and the physical work nature, that make production fields one of the most dangerous working environments. Analysts indicate that IoT technologies can help worksite operators implement additional safety programs and support risks management to prevent and reduce the number of uncontrolled accidents.

IoT technologies can be used to sense disaster signals in order to make early warning, forecast and
predicate dangers, and improve safety in production. A particularly effective application is the automatic equipment shutdown when a proximity sensor detects that a worker has gotten too close by using IoT tags on workers and equipment. In one application, a wireless gas detection sensor network was used to measure the gas concentration in a mining environment [47]. The proposed system considered the airflow direction and ventilation to show the gas distribution in the field. This solution promises production safety by eliminating the risks and dangers of exceeding gas concertation by generating feedback to the ventilation system.

3E.     Research and Development

IoT systems generate a wealth of information of actual usage data. The accumulated information banks can be potentially used to develop new components, avoid specific failures, eliminating unused features and suggest appropriate models. Real-time usage and historical data provide a unique view of the field operations, and present insights for upgrades, addons, the business need for other types of machinery, or equipment replacement. In [48], A fuzzy-logic algorithm is implemented on the existing wireless sensor network for collecting and monitoring underground coal mine data, such as temperature and concentrations of various gases like CO, CO2 and O2. The algorithm feeds the monitored data in a computational model and works as a fire detection system in order to alleviate the fire hazard in a mining environment.

4. IoT Spectrum

The Australian Communication and Media Authority (ACMA) report “The Internet of things and the ACMA’s areas of focus” [49], concentrate on the available spectrum to accommodate M2M (Machine to Machine) and IoT applications within the existing licensing framework and identify candidate spectrum bands to address expected future demand.

Fig. 3 shows the spectrum identified for IoT applications, the spectrum planning approach is outlined in the ACMA’s five-year spectrum outlook [50].

ACMA has licensing arrangements in place that adequately encourage innovation in IoT via the class licensing regime.

Fig. 3 Spectrum identified for IoT applications in Australia.

Class licences authorise users of designated segments of the spectrum to operate on a shared basis. Class licences do not have to be applied for, and no licence fees are payable. The existing IoT spectrum that is globally available at no cost is the Industrial Scientific Medical (ISM) bands, which include the 900 MHz band, the 2.4 GHz band and the 5.8 GHz band. Access to these bands is governed by the Radiocommunications (Low Interference Potential Devices) Class Licence 2015 [51]. The LIPD Class licence defined the items and conditions to permit IoT type operations, such as maximum EIRP, latency, data rate, etc. For example, LIPD class licence limit the maximum transmission power on the ISM bands as follows, 1W for 900MHz, and 4W for 2.4GHz and 5.8GHz.

The advantage of operating on the unlicensed spectrum is that the deployment is not restricted by the availability of the spectrum due to the widely available and free unlicensed spectrum. However, unlike other forms of radio communication licensing (namely apparatus and spectrum licences) that are issued and used on an individual basis, use of this type of ‘licence exempt’ spectrum has the potential of increased possibility of interference, no guarantee for service quality, lower allowable transmission power and compromise in performance.

Private licensing ensures Quality of Service (QoS) management in comparison to best effort unlicensed bands (ISM) and a wider coverage area is achieved via cellular IoT architecture. This is mainly due to operation on dedicated spectrum (normally owned by the licensee) and the use of higher power levels.

An example of this is the IoT cellular applications that are supported in private networks owned by private entities.

5. IoT Implementation Challenges

It is broadly accepted that the IoT technologies and applications are still undergoing development phases [52], and there are many industrial challenges not adequately addressed such as compatibility, standardisation, security and privacy. The lack of integrated solutions from hardware to application level is a barrier for fast adoption. Appropriate integration checks, gap analysis and business application requirements studies are a few of the essential requirements to understand the industry characteristics and ensure a ‘good fit’ IoT technology.

Capturing the maximum value of IoT systems is the result of adequately addressing raised challenges, such as:

  • Interoperability between IoT systems. Demonstrated by the wide range of technologies, the number of interconnected devices and sensors, mobility, decentralisation and complexity of IoT networks architecture. All of which introduce the challenge in data integrations over different environments
  • The IoT standard is relatively complicated and includes architecture standards, communication protocol standards, identification standards, security standards, application standards, data standards, information processing standards and public service platform standards.
  • Policies, intellectual property and business-to-business (B2B) applications to enable prediction, automation and optimisation. Users and business privacy become a security issue. Because of the combinations of things, services, and networks, information management in IoT must cover many objects and levels compared to a traditional network.
  • Legacy systems and communication mechanisms with specific dependencies may introduce barriers or even block the migration of IoT systems to the most economical and efficient platforms.
  • Alternative technologies, product competition in the IoT market and the different computing models are some of the factors that broaden the choice range and results in decision uncertainty. Examples of choices include the availability requirements, fault tolerance and the computational ability of a service, such as SaaS (Software as a Service) [53], PaaS (Platform as a Service) [54], and IaaS (Infrastructure as a Service) [55].
  • Exploration of the many possibilities and elimination of uncertainties, in order to map a clear and mature technical requirement in support of the business model. This is strongly dependent on the organisation internal capabilities to support a business strategy, new processes and systems operation.
  • Multi-layered security designs, represented by the things, services and networks. IoT security must cover additional management objects and levels compared to traditional network security.

6. Theoretical Strategy Framework

Previous researchers have raised questions about factors impacting IoT implementation and methods/ techniques are used to overcome these obstacles [56-59]. Below is one example of a theoretical framework to support strategic decision-making in the context of IoT [60].

The framework model can be used to define the business goals in order to gain a competitive advantage, the model is classified as follows:

  • Managers’ strategic intent: The rapid changes in IoT business models and the shortage of standardisation across IoT products, forces a ‘get-ahead’ and ‘catchup’ strategic management perspectives. The choice of a strategic intent formulates the plans and actions for an organisational IoT development or innovation.
  • Industrial driving force: This step defines the drivers for potential investment in IoT technology.
    Market insights and promotion of IoT technology is made through R&D, or as an integrated part of other enabling technologies (i.e. Autonomy [61], Cloud computing [62], etc.). The high expectations and enormous demands have set unprecedented IoT opportunities, where potential investment in the right direction is predicted to bring substantial advantages to the business.
  • Organisational capabilities: Demonstrated by the knowledge, skills and ability to refine or develop an existing IoT technology. Organisational capabilities also include the exploration of new techniques that have uncertain or distance outcomes.
  • Information gathering and sharing: Represented by the ability to acquire and share information
    internally and externally in order to support the organisation key capabilities and its business model strategy. This includes previous studies, learning processes and market analysis shared between strategic partners.

The Titan ICT project lifecycle model based is selected to provide a high-quality service that incorporates the above define stages for IoT business model. Titan ICT project model is based on the Systems Engineering V-Model, as shown in Fig. 4. The model has been divided into the three sections; Business and Technology Strategy Alignment, Technology Selection and Evaluation, System Engineering and Project Delivery. Depending on the stage of the project, each stage can be performed independently; however, it is recommended that the disciplines occur in sequence.

The left-hand side of the model provides the project definition functions, with the project test and integration occurring on the right-hand side. Validation is performed to ensure that the solution meets the needs, while verification ensures that the method to do so is correct. The key to this approach is defining the problem before a solution is identified.

This model draws from Titan ICT’s extensive library of methodologies, frameworks and tools to ensure the successful delivery of consulting services.

Figure 4: Project lifecycle model.

7. Conclusion

IoT technologies offer immense value and support the enhancement of a business model in operational fields. Research has shown that mining and gas companies that have made IoT investments are reporting positive results. IoT technologies are used to enable automation, streamline engineering processes, reduce downtime and provide transparency at every layer of the operation. IoT data enables solution architects to upgrade designs and prevent historical irregularities.

In addition to the design and implantation challenges of IoT networks, the overwhelming IoT market increases the difficulty of making a strategic business decision. Titan ICT’s engineering model and framework supports identifying business requirements and delivering the stakeholder’s vision. The outcome usually involves detailed recommended steps and procedures to streamline operations and cater for expected growth.

About Titan ICT

Titan ICT is an Australian-owned company specialising in strategic ICT advice, systems integration and technical support services to deliver high quality integrated technology and business solutions. With a proud record of delivery since 2003, we have a national footprint with offices located Perth, Brisbane, Melbourne and Sydney. From the outset the decision was made to focus purely on ICT disciplines providing trusted advice and engineered solutions that tackle technology transformation and maximise the potential of any

project, big or small. As a result, we are at the forefront of new technologies by constantly turning to innovation and ingenuity for the development of tailored, leading-edge solutions that support the operational and strategic objectives of the companies we work with. By working with us, you too can enjoy the success

that results from the bringing together of worldclass skills, best in breed products and practical know-how in planning, managing and delivering complex scopes of work.

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The author only represents himself as competent professional in the planning, design and implementation of Telecommunications and Information Technology systems, networks and practice. Any statement provided which may be of a legal nature is only offered as an opinion based on the author’s understanding of the law and how it may apply. The author has made every effort to identify all relevant and available source data in the preparation of this document. All surveys, forecasts, projections and recommendations are made in good faith on the basis of information available at the time. The author, its agents, licensee and/or other representatives disclaims any liability for loss of damage caused by errors or omissions, whether such errors or omissions resulted from negligence, accident or other causes. Neither the author, its agents, licensee nor representatives will be liable for any loss or other consequences (whether or not due to the negligence of the author or their agents) arising out of the use of information in this report. No responsibility is taken for the accuracy of this information in relation to pricing or functionality of products and services described in this report. Readers should confirm with the appropriate service provider as to the validity of the information and any variations which may have taken place since publishing.