Optimization of an Intelligent Autonomous Drilling Rig: Testing and Implementation of Machine Learning and Control Algorithms for Formation Classification, Downhole Vibrations Management and Directional Drilling

Master's thesis in Petroleum EngineeringIn recent years, considerable resources have been invested to explore applications for- and to exploit the vast amount of data that gets collected during exploration, drilling and production of oil and gas. Such data will potentially become a game changer for the industry in terms of reduced costs through improved operational efficiency and fewer accidents, improved HSE through strengthened situational awareness, ensured optimal placement of wells, less wear on equipment and so on. While machine learning algorithms have been around for decades, it is only in the last five to ten years that increased computational power along with heavily digitalized control- and monitoring systems have been made available. Considering the state of art technology that exists today and the significant resources that are being invested into the technology of tomorrow, the idea of intelligent and fully automated machinery on the drill floor that is capable of consistently selecting the best decisions or predictions based on the information available and providing the driller and operator with such recommendations, becomes closer to a reality every day. This thesis is the result of research carried out on the topic of drilling automation. Its basis has been improvements and upgrades conducted on a laboratory-scale drilling rig developed at the University of Stavanger, as part of the multi-disciplinary project; UiS Drillbotics. Main contribution of the thesis is a study on how machine learning can be used to develop models that are capable of accurately predicting what rock formation is being drilled using an autonomous control system, along with detecting some common drilling incidents in real-time on the laboratory rig. Methodology is also applied to field data from the Volve field. Furthermore, research and implementation of search algorithms to ensure optimal drilling speed (ROP), safety to personnel and environment (HSE), and efficiency along with a digitalized drilling program for directional drilling, gets presented. Finally, rig upgrades for directional drilling and research into downhole sensors that get used in a closed-loop steering model is elaborated on.submittedVersio

Data-Driven Approaches Tests on A Laboratory Drilling System

In recent years, considerable resources have been invested to exploit vast amounts of data that get collected during exploration, drilling and production of oil and gas. Data-related digital technologies potentially become a game changer for the industry in terms of reduced costs through increasing operational efficiency and avoiding accidents, improved health, safety and environment through strengthening situational awareness and so on. Machine learning, an application of artificial intelligence to offer systems/processes self-learning and self-driving ability, has been around for recent decades. In the last five to ten years, the increased computational powers along with heavily digitized control and monitoring systems have made machine learning algorithms more available, powerful and accurate. Considering the state-of-art technologies that exist today and the significant resources that are being invested into the technologies of tomorrow, the idea of intelligent and automated drilling systems to select best decisions or provide good recommendations based on the information available becomes closer to a reality. This study shows the results of our research activity carried out on the topic of drilling automation and digitalization. The main objective is to test the developed machine learning algorithms of formation classification and drilling operations identification on a laboratory drilling system. In this paper, an algorithm to develop data-driven models based on the laboratory data collocated in many scenarios (for instance, drilling different formation samples with varying drilling operational parameters and running different operations) is presented. Moreover, a testing algorithm based on data-driven models for new formation detection and confirmation is proposed. In the case study, results on multiple experiments conducted to test and validate the developed machine learning methods have been illustrated and discussed.publishedVersio

Hydration in fluorite-related rare-earth cerates

Hydration enthalpy and water uptake in La2-xNdxCe2O7 series (x = 0.0, 0.5, 1.0 and 2.0) have been measured using combined thermogravimetry (TG) and differential scanning calorimetry (DSC), TG-DSC. The DSC data unambiguously yield standard molar hydration enthalpies of around -74 kJ/mol independent of water uptake. The TG results however needs interpretation according to a model, and it is clear that they cannot be fitted to a classical model of hydration of all disordered oxygen vacancies. Instead, the hydration appears to be limited to a small fraction of the free vacancies. Hydration further decreases as the Nd content (x) and long range order increases and regions of disorder decrease. We propose a new model explaining why hydration occurs only in a small fraction of the nominally free vacancies: The higher basicity of La/Nd compared to Ce enables hydration, and high coordination with La/Nd around OH is needed to stabilize the proton/hydroxide in order to obtain exothermic hydration. The statistical variation of coordination around oxygen sites in a disordered fluorite oxide creates a limited number of such oxide ions sites which results in limited hydration. It is expected that this new purely statistical approach to interactions in special cases of heavily defective compounds may apply to rationalize unexpected defect behavior also in other systems

Correlations between standard accelerated tests for protective organic coatings and field performance

Accelerated testing is widely used in development and pre-qualification of protective organic coatings. In this work 26 coating systems have been investigated in a 2-year C5 atmospheric exposure field test, ISO 9227 salt spray test, ISO 12944-9 cyclic ageing and ISO 16773 electrochemical impedance spectroscopy measurement of coating resistance. Of the 26 coating systems, 16 have epoxy mastic primers and 10 have zinc rich epoxy primers. In the field test, the zinc rich primer improved corrosion creep resistance from scribe by a factor of about 10. However, this is not reflected in any of the accelerated lab tests. The lab tests all show rather poor correlation to the field test with respect to corrosion creep. All the coatings had little corrosion creep from scribe in the field test, even the coating systems with epoxy mastic primers. The large focus on this parameter in coating pre-qualification testing, e.g. in ISO 12944-6 and 12944-9, may therefore not be justified.publishedVersio

Hydration thermodynamics of oxides. Effects of defect associations

Mye av dagens høyteknologiske utstyr og apparater ville sannsynligvis ikke sett dagens lys hvis ikke det hadde vært for materialteknologiens stadige fremskritt. I jakten på stadige forbedringer av slik teknologi må man forstå og påvirke materialenes funksjonelle egenskaper. Deres egenskaper er i stor grad bestemt av defekter i krystallstrukturen, hvor man ved hjelp av defektkjemi kan uttrykke defektenes konsentrasjoner ved forskjellige betingelser. I denne avhandlingen har Løken sett nærmere på defektkjemien til flere akseptordopede protonledende oksider ved hjelp av en rekke eksperimentelle teknikker og kvantemekanisk modellering. Slike oksider er av stor interesse for hydrogensamfunnet, hvor de blant annet kan være aktuelle komponenter i en brenselcelle eller elektrolysør ved høyere temperaturer. Arbeidet har vist at mange av egenskapene til slike oksider vil være sterkt påvirket av defektinteraksjoner, spesielt mellom akseptoren og de positivt ladede protonene og oksygenvakansene. Blant annet vil både mengde og type akseptor gi opphav til helt forskjellig hydratiseringstermodynamikk og protonledningsevne. Det ble også vist at syntesebetingelsene kan være avgjørende for graden av defektassosiering i oksider, noe som kan forklare en del av uoverensstemmelsene i litteraturen. Arbeidet i sin helhet understreker den kritiske rollen til akseptordopanten i oksider, som er av stor betydning i videreutviklingen av denne type oksider i fremtidig teknologi

Thermodynamics and transport of defects in Sc-doped CaSnO3 and CaZrO3

Correlations aimed at linking the hydration thermodynamics to materials parameters can be of vital importance for further development of proton conducting oxides. However, the currently proposed correlations are to a large degree troubled by scattering limiting their predictive power. As such, the present contribution has investigated Sc-doped CaSnO3 and CaZrO3 in an attempt to further elucidate the thermodynamic trends of hydration in perovskites. The defect structure and conductivity of polycrystalline samples of CaSn0.95Sc0.05O3-δ and CaSn0.9Sc0.1O3-δ has been studied by AC impedance measurements in the temperature range 150-1100 °C. The majority defects were characterised by measuring the conductivity as a function of p(H2O) and p(O2). These indicated that both samples are predominantly oxygen ion conducting with a protonic contribution under wet conditions at 300-400 °C for CaSn0.9Sc0.1O3-δ. Under oxidising conditions at elevated temperatures of 1000 °C and above, the conductivity is dominated by electron holes. The p(H2O) dependencies at temperatures of 300-500 °C for CaSn0.9Sc0.1O3-δ were modelled based on a simplified defect structure resulting in an extracted hydration enthalpy and entropy of -41 ± 5 kJ mol-1 and -107 ± 7 J K-1 mol-1, respectively. Impedance spectroscopy was conducted in the temperature range 150-700 °C in order to study the hydration processes in the grain boundaries of Sc-doped CaSnO3. It was demonstrated that the grain boundary conductivity exhibited a larger contribution from protons than the bulk at temperatures below 400 °C. These differences were suggested to be due to the presence of inherent space charge layers depleting the oxygen vacancies. The depletion of oxygen vacancies was more severe for CaSn0.95Sc0.05O3-δ than CaSn0.9Sc0.1O3-δ, which is consistent with a smaller segregation of acceptors compensating the positively charged grain boundary core. Simultaneous thermogravimetry (TG) and differential scanning calorimetry (DSC), TG-DSC, was applied to measure the standard molar hydration enthalpies and entropies of CaSn1-xScxO3-δ and CaZr1-xScxO3-δ as a function of the concentration of Sc. It was demonstrated that both the hydration enthalpy and entropy become increasingly negative with increasing Sc substitution. The thermodynamic parameters were in agreement with the values from literature and the results from conductivity measurements and TG. The values were also demonstrated to be consistent with respect to temperature (500-900 °C) and p(H2O) (0.1-1 atm). This suggests that TG-DSC can be used for the evaluation of hydration thermodynamics in oxides. The obtained thermodynamic parameters of hydration from TG-DSC were compared with available literature values of other perovskites in an attempt to correlate the values to materials properties. While the hydration enthalpy was found to be in good agreement with the basicity of the oxide, the hydration entropy exhibited a dependence to the vibrational wavenumber of the OH stretching mode (νOH). As the two are interrelated properties, it suggests a correlation between the thermodynamic parameters of hydration, as was demonstrated in both materials studied

A study of entrance to the Chinese cloud computing market for AppsCo

This thesis is a result of a cooperation with AppsCo. AppsCo is a cloud computing provider. The company host and provide the infrastructure and technology required to be able to offer and access the cloud service. The aim of this report has been to map out the cloud computing market in China, find out if there is a market for their solutions and if AppsCo should enter China. The thesis has analysed the cloud computing industry in China and its most important players. From the competitor analysis it becomes clear that there are no competitors that offers all the same solutions as AppsCo. However, there are several national and international competitors such as Amazon AWS, Microsoft Azure and Aliyun that offer similar solutions as Appsco. Through the internal scan of AppsCo, it becomes clear that their financial resources are limited, further development of the solutions are required and key management people do not have the capacity to be present in the market. This will effect the recommendation for a suitable entry strategy. It also becomes clear in the thesis that AppsCo furfils all the criterias of a born global. The discussion about AppsCo being a born global is based on the in-depth internal analysis conducted. Secondary research together with interviews based on the Delphi method, has been conducted in order to gain a deeper understanding of the cloud computing market in China. The findings indicate that there is enthusiasm among the customers for the solutions that AppsCo provides. The results from secondary and primary research made the foundation for the evaluation of two entry strategies for AppsCo. Based on the internal and external analysis combined with more in depth secondary research and Delphi interviews, the recommendation for AppsCo is to develop their solutions and strengthen their finance, before entering the Chinese market. When this is done the most suitable entry strategy for Appsco is through a WOFE

Thermal and Chemical Expansion in Proton Ceramic Electrolytes and Compatible Electrodes

This review paper focuses on the phenomenon of thermochemical expansion of two specific categories of conducting ceramics: Proton Conducting Ceramics (PCC) and Mixed Ionic-Electronic Conductors (MIEC). The theory of thermal expansion of ceramics is underlined from microscopic to macroscopic points of view while the chemical expansion is explained based on crystallography and defect chemistry. Modelling methods are used to predict the thermochemical expansion of PCCs and MIECs with two examples: hydration of barium zirconate (BaZr1−xYxO3−δ) and oxidation/reduction of La1−xSrxCo0.2Fe0.8O3−δ. While it is unusual for a review paper, we conducted experiments to evaluate the influence of the heating rate in determining expansion coefficients experimentally. This was motivated by the discrepancy of some values in literature. The conclusions are that the heating rate has little to no effect on the obtained values. Models for the expansion coefficients of a composite material are presented and include the effect of porosity. A set of data comprising thermal and chemical expansion coefficients has been gathered from the literature and presented here divided into two groups: protonic electrolytes and mixed ionic-electronic conductors. Finally, the methods of mitigation of the thermal mismatch problem are discussed

On the relationship between chemical expansion and hydration thermodynamics of proton conducting perovskites

In this contribution, we determine the compositional dependence of the chemical expansion and entropy of hydration of the proton conducting perovskites BaZrO3, BaSnO3, BaCeO3, and SrZrO3 by first principles phonon calculations. The calculations reveal that the cubic BaZrO3 and BaSnO3, which display the least favourable hydration enthalpies, −72 and −65 kJ mol−1, respectively, exhibit the most favourable entropies, −108 and −132 J mol−1 K−1, respectively. The strong compositional dependency of the hydration entropy primarily originates from the entropy gain upon filling the oxygen vacancy, which is closely related to the chemical expansion coefficient of oxygen vacancies, and thus the chemical expansion upon hydration. The chemical expansion coefficient of oxygen vacancies is more negative for the cubic than the orthorhombic perovskites, leading to a considerably larger chemical expansion upon hydration of the former. The calculations therefore suggest that challenges associated with chemical expansion upon hydration of BaZrO3 proton conducting electrolytes to some extent can be avoided, or reduced, by partial substitution of Zr by Ce

Unravelling the fundamentals of thermal and chemical expansion of BaCeO3 from first principles phonon calculations

Differentiating chemical and thermal expansion is virtually impossible to achieve experimentally. While thermal expansion stems from a softening of the phonon spectra, chemical expansion depends on the chemical composition of the material. In the present contribution, we, for the first time, completely decouple thermal and chemical expansion through first principles phonon calculations on BaCeO3, providing new fundamental insights to lattice expansion. We assess the influence of defects on thermal expansion, and how this in turn affects the interpretation of chemical expansion and defect thermodynamics. The calculations reveal that the linear thermal expansion coefficient is lowered by the introduction of oxygen vacancies being 10.6 × 10−6 K−1 at 300 K relative to 12.2 × 10−6 K−1 for both the protonated and defect-free bulk lattice. We further demonstrate that the chemical expansion coefficient upon hydration varies with temperature, ranging from 0.070 to 0.115 per mole oxygen vacancy. Ultimately, we find that, due to differences in the thermal expansion coefficients under dry and wet conditions, the chemical expansion coefficients determined experimentally are grossly underestimated – around 55% lower in the case of 10 mol% acceptor doped BaCeO3. Lastly, we evaluate the effect of these volume changes on the vibrational thermodynamics