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Jackson, A. C. (Chevron Corporation) | Dean, R. M. (Chevron Corporation) | Lyon, J. (Chevron Corporation) | Dwarakanath, V. (Chevron Corporation) | Alexis, D. (Chevron Corporation) | Poulsen, A. (Chevron Corporation) | Espinosa, D. (Chevron Corporation)
Reservoir management for an economically successful chemical EOR project involves maintaining high injectivity to improve processing rates. In the Captain Field, horizontal injection wells offshore have been stimulated with surfactant-polymer fluids to reduce surrounding oil saturations and boost water relative permeability. The surfactant-polymer stimulation process described herein enables a step change in injectivity and advances the commercialization of this application. This paper explains the damage mechanism, laboratory chemical design, quality control through offshore field execution and data quantifying the results.
Phase behaviour laboratory experiments and analytical injectivity models are used to design a near wellbore clean-up and relative permeability improvement. Three field trials were conducted in wells that had observed significant injectivity decline over 1-3 years of polymer injection. Surfactant and polymer are blended with injection water and fluid quality is confirmed at the wellheads. Pressure is continuously monitored with injectivity index to determine the chemical efficiency and treatment longevity. Oil saturation changes and outflow profile distributions are analysed from well logs run before and after stimulating. Learnings are applied to refine the process for future well treatments.
The key execution elements include using polymer to provide adequate mobility control at high relative permeability and ensure contact along the entire wellbore. Repeatability of success with surfactant-polymer injection is demonstrated with decreased skin in all the wells. The key results include the oil saturation logs that prove the reduction of oil near the well completion and improves the relative permeability to aqueous phase. The results also prove to be sustainable over months of post-stimulation operation data with high injectivity.
Injectivity enhancement was supported by chemical quality control through the whole process. From laboratory to the field (from core flood experiments to dissolution of trapped oil near wellbore), surveillance measurements prove that the chemical design was maintained and executed successfully. The enhanced injectivity during clean-up allows for higher processing rate during polymer injection and negates the need for additional wells.
The application of surfactant-polymer technology can rejuvenate existing wells and avoid high costs associated with redrilling offshore wells. This improves processing rate for EOR methods and can even be applied to waterflood wells to improve the injectivity, e.g low permeability reservoirs.
A Digital Twin is a software representation of a facility which can be used to understand, predict, and optimize performance to help to achieve top performance and recover future operational losses. The Digital twin consists of three components: a process model, a set of control algorithms, and knowledge.
Usually the time for commissioning a project exceeds the initial estimations, therefore delays in project completion are quite common. This is often because ICSS testing is done on a static system which does not account for how the system will react dynamically to certain scenarios such as start-ups and shutdowns. Issues such as configuration errors, loop behaviors, start-up over-rides, dead-lock inter-trips and sequence logic are difficult to predict and are impossible to anticipate during static testing. Such delays lead to higher costs and therefore reduced revenue.
This paper aims to describe the most innovative approach to Project & Operational Certainty, which addresses these issues by using a Digital Twin for commissioning support and training. One successful use of this approach was in the Culzean project, an ultra-high-pressure high temperature (UHP/HT) gas condensate development in the UK sector of the Central North Sea. A high-fidelity process model was built and fitted to the actual plant performance based on equipment data sheets. This was connected to ICSS database and graphics, offering a realistic environment, very close to the one offshore, which had the same look and feel for the operators.
Dynamic tests conducted on the Digital Twin predicted issues on the real system, which enabled potential solutions to be tested, leading to a significant decrease in the time spent and cost during commissioning. All the operating procedures were dynamically tested, which enabled us to correct errors, saving time before First Gas. Additionally, all CRO (Control Room Operators) and field technicians were trained and made familiar with the system months in advance, aiming to avoid future unnecessary trips during First Gas.
Finally, all the control loops were fine tuned in the Digital Twin and parameters were passed to off shore, to be used as first starting point. It is expected that these parameters will be very close to fine operational points, as the model used is high fidelity model and very close to real system offshore.
Yudhowijoyo, Azis (University of Aberdeen) | Rafati, Roozbeh (University of Aberdeen) | Sharifi Haddad, Amin (University of Aberdeen) | Pokrajac, Dubravka (University of Aberdeen) | Manzari, Mehrdad (University of Aberdeen)
Crosslinked polymer gels have been widely used to overcome water and gas coning problem in the petroleum industry. Recently, nanoparticles are identified to have a potential of reinforcing the polymer gel systems by improving physical bonding and heat transfer properties in the gel structure. In this study, silicon dioxide and aluminium oxide nanoparticles were introduced to xanthan gum polymers that were crosslinked by chromium (III) acetate, to create polymeric nanocomposite gels with higher shear strengths. The gelation time and gel strength have been selected as main parameters to evaluate the effect of nanoparticle types and concentrations on the nanocomposite gels performance. The gelation time is measured until the onset of gelation or the moment when apparent viscosity starts to increase at 60°C. The gel strength is represented by the storage modulus (G’) after 24 hours of gelation at 60°C. Both parameters were measured by a rheometer, through constant shear rate and oscillatory tests respectively.
The addition of 1000 and 10000 ppm of silicon dioxide (SiO2) nanoparticles into a solution of 6000 ppm xanthan gum polymers that are crosslinked with 50000 ppm chromium (III) acetate caused insignificant changes in gelation time. Similar result was also reported when 1000 and 10000 ppm of aluminium oxide (Al2O3) nanoparticles was introduced into the polymer system. This suggests that when SiO2 and Al2O3 nanoparticles are introduced to xanthan/chromium (III) Acetate system for field application, no additives would be required to prolong or shorten gelation time to counter the nanoparticles addition. To analyse the gel strengths, the results from the oscillatory test were averaged throughout the frequency range, and it was shown that the addition of SiO2 nanoparticles decreases the average storage modulus from 75.1 Pa without nanoparticles, to 72.3 Pa at the nanoparticles concentration of 1000 ppm. However, the average storage modulus increased to 83.0 Pa and 94.7 Pa at higher nanoparticles SiO2 concentrations of 5000 ppm and 10000 ppm. The same trend was observed for the nanocomposite gels that were produced by Al2O3 nanoparticles. Similarly, the storage modulus decreased initially to 70.8 Pa at the concentration of 1000 ppm, then it increased to 89.9 Pa and 109.4 Pa at nanoparticles concentrations of 5000 pm and 10000 ppm, respectively. Hence, the nanoparticle-enhanced biopolymer gels showed insignificant changes of gelation time, and at the same time, they demonstrated up to 45% improvements in the gel strength properties when the nanoparticles concentration is higher than 5000 ppm.
In conclusion, the nanocomposite gels demonstrated reinforced bonding properties and showed higher gel strengths that can make them good candidates for leakage prevention from gas wells and blocking of water encroachments from aquifers into the wells.
This paper presents a Digital Twin concept aimed at assets in the oil & gas and wind industry, that provides an accurate estimate of the true fatigue life of these assets in order to unlock potential fatigue life and ultimately extend the life of assets. This concept is divided in four tiers that allow to unlock remaining fatigue life one after the other. The first tier consists of using a high-resolution finite element model of the asset, delivered by Akselos unique RB-FEA technology. The subsequent tiers consist in using data from a few strategically placed accelerometers, as well as wave radar recordings, in order to calibrate the model and estimate the real loading on the asset. This concept delivers a true digital twin of the asset and offers a compelling and costeffective method for offshore assets that are facing life time extension beyond what current methodologies can provide. The concept is being implemented on one of Shell's platforms in the Southern North Sea.
Objectives/Scope: The realization that fossil fuels are a limited resource, and the growing awareness of the negative impact their emissions have on the planet, has impacted every oil and gas major. The global challenge is expressed in the "energy trilemma" of: Enough Energy, Affordable Energy and Sustainable Energy. The industry must adapt, in terms of cost and environmental footprint. In this paper we discuss how digitalization and renewable sources can drive innovation to meet these challenges. Methods, procedures, process: We will use current long-range forecasts to understand how the global energy mix is expected to change over time, and illustrate how different scenarios are likely to affect the offshore industry. We also study how digitalization and hybridization with technologies like offshore wind and power-from shore, can reduce costs, energy consumption and emissions. Results, Observations and Conclusions: There are many trends accelerating the introduction of new energy sources These include: 1. Global population growth and changing dynamics: "Millennials" bring with them their own expectations about technology, the pace of work and accountability. Equally influential, is the challenge to feed and power the 2 billion poorest and the extra 2 billion people expected by 2050.
Significant advancements in physics-based model development, software workflow practices, multi-core processing and cost-effective cloud computing has enabled the adoption of high fidelity, three-dimensional (3D) modeling such as computational fluid dynamics (CFD), finite element analysis (FEA), and other first principles-based analyses into normal engineering design practices. Historically, integration of these tools into the standard engineering workflow was challenging due to the excessively long turnaround times to deliver any results. Three Case Studies are subsequently presented where 3D modeling analysis was used early and seamlessly in the engineering design process to solve problems related to consequence analysis and equipment operational performance: Case 1) Risk assessment of pilot flame extinguishment due to inert gas discharge from the flare of an FPSO, Case 2) Jet dispersion analysis from HP/LP flare to assess hydrocarbon and H 2 S concentrations at critical locations on the platform, including results comparison between CFD results and a conventional dispersion tool - Flaresim, and, Case 3) Solving a fatigue induced cracking problem on the cooling water circuit of a heat exchanger using an integrated workflow consisting of CFD modelling of the cooling water, stress analysis using FEA, and structural integrity assessment per ASME BPVC VIII Division 2. The modelling results from these case studies were generated in timeframes similar to those using conventional engineering calculation methods, and thus allowed for prompt integration into the engineering design process without impacting project schedules and delivery. Moreover, the costs to perform these modelling analyses were not substantially greater than the costs associated with conventional calculation methods, thereby providing high value to the engineering projects.
Recovery and valorization of wasted gas associated to methane processing (i.e. leakages from rotating equipment and flared gas) has usually been avoided due to the inherently limited amount of gas of these streams. Moreover, the technical complexities are further enhanced when applied to aging infrastructures and old compression unit designs, making the solution complex and less cost-effective.
However, emission control regulation is progressively limiting the atmospheric release of gases from the hydrocarbon production and processing. These requirements have triggered the development of new technical solutions to limit even small gas streams typically neglected in the past. Typical examples of small leakages tolerated in gas processing are associated with the Dry Gas Seals (DGS) primary vents. The limited amount of gas released did not justify a recovery system, leaving flaring as the only viable option.
In this paper, the technical solutions for compressor DGS primary vent recovery are presented, with further discussion on the integration into the gas process. Financial sustainability of the solutions is also presented, with the analysis of two selected cases. The presented solutions are designed to reflect the positive impact of wasted gas reduction, contributing to reaching environmental sustainability targets in oil and gas.
This paper will discuss when it is advantageous (in the context of an offshore oil and gas environment) to process data at the network edge (in close proximity to equipment assets) or to stream data to a cloud-based Internet of Things (IoT) platform for analysis. It will offer an objective assessment of both approaches and provide recommendations for securing data in both cases, as part of an overarching cybersecurity strategy.
IoT has opened the door to significant efficiency gains in the oil and gas industry. This is particularly the case in the offshore sector, where there is a pressing need to reduce costs and maximize equipment availability. In some cases, it is advantageous to process data in close proximity to equipment assets (i.e., at the edge). In others, it makes more sense to securely stream data to a cloud- based IoT platform and harness artificial intelligence (AI) to aid in decision making. In certain cases, both architectures can be utilized in compliment to one another.
Many factors need to be taken into consideration when evaluating an edge or cloud-based approach. Some of these include data volume, transmission and processing speed, control of data, cost, etc. Edge computing can be used to streamline and enhance the efficiency of data analytics. In certain applications, this can mean the difference between analyzing a performance failure after the fact, and pre-empting it in the first place, which in the offshore environment could potentially translate into millions of dollars per day.
On the other hand, there are situations where it is beneficial to store large volumes of data on a cloud-based platform. For example, if the goal is to leverage advanced IoT-based industrial analytics to optimize an entire fleet of a certain type of equipment, the cloud may be the best solution. Cybersecurity is another consideration. Attacks on critical infrastructure have risen significantly over the course of the past year. As more Intelligent Electronic Devices (IEDs) are deployed in the oil and gas industry to optimize efficiency, Industrial Control Systems (ICSs) are increasingly vulnerable. As a result, the threat extends beyond proprietary data to mission-critical operational technology (OT) assets and equipment.
Cybersecurity standards and layered, defense-in-depth models have grown in response to the frequency and sophistication of cyber attacks. Additionally, recent advances in cyber defense technology incorporate small, kilobit-sized embedded software agents to monitor networks for anomalies that could signal an intrusion. This paper will explore new cybersecurity threats to oil and gas assets, as well as strategies operators can employ to defend against them, whether using an edge or cloud-based platform, or both.
Nine years have passed since the Deepwater Horizon disaster and industry is in a considerably better position to respond to a loss of well control of that scale. With the delivery of the Offset Installation Equipment (OIE) in January 2018 the joint industry Subsea Well Response Project (SWRP) has drawn to a close. Despite this, equipment and services continue to be developed. This paper will communicate developments in subsea well response technologies and the latest guidance developed by industry.
This paper provides an overview of the International Oil and Gas Producers (IOGP) Report 594 - Source Control Emergency Response Planning Guide for Subsea Wells. What should a comprehensive subsea Source Control Emergency Response Plan (SCERP) consider? What resources including manpower, expertise and equipment would be required for a controlled response? In addition, it provides an overview of recent enhancements in subsea well response equipment. This includes; offset installation equipment (OIE) for shallow water scenarios where vertical access above a wellhead may not be possible and air-freight capping stack solutions to minimise incident country configuration and testing.
The findings from technical and logistical studies, whilst developing this technology, will be clearly communicated for industry consideration. This includes critical activities to be considered in developing response times models. This paper will demonstrate that capping equipment located in country does not necessarily improve the overall response time for a loss of well control event; an effectively planned response is more important than immediate hardware availability. The importance of mutual aid of personnel and equipment in a response will be key as not one company can provide all the solutions.
Although only required for remote or land locked basins, to further enhance industries capabilities, it has recently been demonstrated that existing ram based capping stacks can be transported by air, without disassembly, and thereby maintaining pressure boundaries. This allows for a more rapid air mobilisation to the incident location without the need for major re-assembly upon arrival.
Shell in the UK has a vast network of more than 200 pipelines & umbilicals covering some 3000 kilometres. Historically, Shell has executed Side Scan Sonar Surveys along these pipelines using a Remotely Operated Towed Vehicle and subsequently followed up with ROV based surveys & inspections. However, in 2018, the respective Geomatics & Subsea Maintenance / Pipelines Departments decided to take advantage of new & emerging innovative technologies and compiled a minimal technical scope & tender document to tap into the latest that the market could offer. Consequently, Shell UK awarded DeepOcean (Norway) with a contract for their "Fast Digital Imaging Service" and embarked on a 45 day survey campaign. In 2019, the same subsea inspection project will be executed once again and the lessons learned ought to inspire and excite many different disciplines and communities, both internally within Shell and externally e.g OGA - Oil & Gas Authority & other valued stakeholders. The paper highlights the key technologies that were deployed and how the new deliverables & business insights take us down the road to Digitalisation including scope for future Machine Learning & Automation processes. Challenges arising from the acquisition and managing the associated data sets shall also be discussed. The speaker will spark dialogue at the end by asking the respective communities how robotics and artificial intelligence will change the industry landscape?