The history of oil well engineering applications has revealed that the frequent operational problems are still common in oil well practice. Well blowouts, stuck pipes, well leakages are examples of the repeated problems in the oil well engineering industry. The main reason why these unwanted problems are unavoidable can be the complexity and uncertainties of the oil well processes. Unforeseen problems happen again and again, because they are not fully predictable, which could be due to lack of sufficient data or improper modelling to simulate the real conditions in the process. Traditional mathematical models have not been able to totally eliminate unwanted oil well problems because of the many involved simplifications, uncertainties, and incomplete information. This research work proposes a new approach and breakthrough for overcoming these challenges. The main objective of this study is merging two scientific fields; artificial intelligence and petroleum engineering in order to implement a new methodology. Case-Based Reasoning (CBR) and Model-Based Reasoning (MBR), two branches of the artificial intelligence science, are applied for solving complex oil well problems. There are many CBR and MBR modelling tools which are generally used for different applications for implementing and demonstrating CBR and MBR methodologies; however, in this study, the Creek system which combines CBR and MBR has been utilized as a framework. One specific challenging task related to oil well engineering has been selected to exemplify and examine the methodology. To select a correct candidate for this application was a challenging step by itself. After testing many different issues in the oil well engineering, a well integrity issue has been chosen for the context. Thus, 18 leaking wells, production and injection wells, from three different oil fields have been analysed in depth. Then, they have been encoded and stored as cases in an ontology model given the name Wellogy. The challenges related to well integrity issues are a growing concern. Many oil wells have been reported with annulus gas leaks (called internal leaks) on the Norwegian Continental Shelf (NCS) area. Interventions to repair the leaking wells or closing and abandoning wells have led to: high operating cost, low overall oil recovery, and in some cases unsafe operation. The reasons why leakages occur can be different, and finding the causes is a very complex task. For gas lift and gas injection wells the integrity of the well is often compromised. As the pressure of the hydrocarbon reserves decreases, particularly in mature fields, the need for boosting increases. Gas is injected into the well either to lift the oil in the production well or to maintain pressure in the reservoir from the injection well. The challenge is that this gas can lead to breakdown of the well integrity and cause leakages. However, as there are many types of leakages that can occur and due to their complexity it can be hard to find the cause or causal relationships. For this purpose, a new methodology, the Creek tool, which combines CBR and MBR is applied to investigate the reasons for the leakages. Creek is basically a CBR system, but it also includes MBR methods. In addition to the well integrity cases, two complex cases (knowledge-rich cases) within oil well engineering have also been studied and analysed through the research work which is part of the PhD. The goal here is to show how the knowledge stored in two cases can be extracted for the CBR application. A model comprising general knowledge (well-known rules and theories) and specific knowledge (stored in cases) has been developed. The results of the Wellogy model show that the CBR methodology can automate reasoning in addition to human reasoning through solving complex and repeated oil well problems. Moreover, the methodology showed that the valuable knowledge gained through the solved cases can be sustained and whenever it is needed, it can be retrieved and reused. The model has been verified for unsolved cases by evaluating case-matching results. The model gives elaborated explanations of the unsolved cases through the building of causal relationships. The model also facilitates knowledge acquisition and learning curves through its growing case base. The study showed that building a CBR model is a rather time-consuming process due to four reasons: 1. Finding appropriate cases for the CBR application is not straightforward 2. Challenges related to constructing cases when transforming reported information to symbolic entities 3. Lack of defined criteria for amount of information (number of findings) for cases 4. Incomplete data and information to fully describe problems of the cases at the knowledge level In this study only 12 solved cases (knowledge-rich cases) have been built in the Wellogy model. More cases (typically hundreds for knowledge-lean cases and around 50 for knowledge-rich cases) would be required to have a robust and efficient CBR model. As the CBR methodology is a new approach for solving complex oil well problems (research and development phase), additional research work is necessary for both areas, i.e. developing CBR frameworks (user interfaces) and building CBR models (core of CBR). Feasibility studies should be performed for implemented CBR models in order to use them in real oil field operations. So far, the existing Wellogy model has showed some benefits in terms of; representing the knowledge of leaking well cases in the form of an ontology, retrieving solved cases, and reusing pervious cases.

Heavy oil is characterized by its high viscosity, which is a major obstacle to both logging and recovery. Due to the loss of T 2 information shorter than the echo spacing ( TE ), estimation of heavy oil properties from NMR T 2 measurements is usually problematic. In this work, a new method has been developed to overcome the echo spacing restriction of NMR spectrometer during the measurement of heavy oil. A FID measurement supplemented the CPMG in an effort to recover the lost T 2 data. Constrained by the initial magnetization ( M 0 ) estimated from the FID and Curie's law and assuming lognormal distribution for bitumen, the corrected T 2 of bitumen can be obtained. This new method successfully overcomes the TE restriction of the NMR spectrometer and is nearly independent on the TE applied in the measurement. This method was applied in the measurement of systems at elevated temperatures (8 ∼ 90 °C) and some important petrophysical properties of Athabasca bitumen, such as hydrogen index ( HI ), fluid content and viscosity were evaluated by using the corrected T 2 . Well log NMR T 2 measurements of bitumen appear to be significantly longer than the laboratory results. This is likely due to the dissolved gas in bitumen. The T 2 distribution depends on oil viscosity and dissolved gas concentration, which can vary throughout the field. In this work, the viscosity and laboratory NMR measurements were made on the recombined live bitumen sample and the synthetic Brookfield oil as a function of dissolved gas concentrations. The effects of CH 4 , CO 2 , and C 2 H 6 on the viscosity and T 2 response of these two heavy oils at different saturation pressures were investigated. The investigations on live oil viscosity show that, regardless of the gas type used for saturation, the live oil T 2 correlates with viscosity/temperature ratio on a log-log scale. More importantly, the changes of T 2 and viscosity/temperature ratio caused by solution gas follows the same trend of those caused by temperature variations on the dead oil. This conclusion holds for both the bitumen and the synthetic Brookfield oil. This finding on the relationship between the oil T 2 and its corresponding viscosity/temperature ratio creates a way for in-situ viscosity evaluation of heavy oil through NMR well logging.

Mineral scale formation is important to many areas of science and engineering, from drinking water treatment to oceanography to oil and gas production. In some cases mineral deposition is beneficial, as in water treatment for heavy metal or arsenic removal, and sometimes it is deleterious, as occurs in oil and gas production due to co-produced water. In either case, understanding the mechanisms of precipitation and inhibition is critical. Work in this thesis has focused on the impact of metal ions on mineral scale formation, and control. The results reveal that the addition of metal ions in the pill solution significantly improved the retention of scale inhibitors. Both BHPMP and DTPMP returns were significantly extended by the addition of Ca 2+ and Fe 2+ Also trace levels of Zn 2+ significantly enhanced the performance and retention of both BHPMP and DTPMP. The enhanced scale inhibition may be caused by a complex of metal ions with amine group of polyamino- polyphosphonates. It is known that the effectiveness of inhibitors varies upon the type of scale formed where it has been mentioned in the literature that common calcium carbonate inhibitors are not effective for preventing iron carbonate. Therefore, this work was also intended to investigate the impact of calcium and iron ions in the co-precipitation of iron-calcium carbonate solid solutions (Fe x Ca 1-x CO 3 ). Three different experimental methods were applied to investigate and predict the precipitation of Fe x Ca 1-x CO 3 : Free drift, continuous feeding, and constant composition experiments. The results from all methods showed that calcium carbonate was kinetically favored to precipitate rather than iron carbonate when the solution is supersaturated with respect to calcium carbonate and iron carbonate. In the constant composition experiments a series of solid solutions of iron-calcium carbonate ranging from calcium-rich to iron-rich was precipitated. Based upon the experimental results and the theoretical derivation, a new model in a form of logistic function was developed to predict the stoichiometry of Fe x Ca 1-x CO 3 as a function of the aqueous solution composition. The model showed an excellent representation for the experimental results with R 2 greater than 0.97 and 0.88 for Fe x Ca 1-x CO 3 and Ba x Ca 1-x CO 3 , respectively. The experimental equipment and procedures described in this work provide an effective means of producing and handling oxygen sensitive solid solutions. The precipitation kinetics of a number of solid solutions in aquatic systems could be studied by adapting the experimental design developed herein.

The focus of this thesis was conducting experiments which would help in understanding mechanisms and in design of surfactant enhanced oil recovery (EOR) processes in various scenarios close to reservoir conditions such as heterogeneity, effects of crude oil, wettability, etc. Foam generated in situ by surfactant alternating gas injection was demonstrated as a substitute for polymer drive in a 1-D FOR process. It was effective in a similar process for a 266 cp crude oil even though the system did not have favorable mobility control. Foam enhanced sweep efficiency in a layered sandpack with a 19:1 permeability ratio. Foam diverted surfactant from the high- to the low-permeability layer. Ahead of the foam front, liquid in the low-permeability layer crossflowed into the high-permeability layer. Foam completely swept the system in 1.3 TPV (total pore volume) fluid injection while waterflood required 8 TPV. When the same 2-D system was oil-wet, the recovery by watertlood was only 49.1% of original oil-in-place (OOIP) due to injected water flowing through high-permeability zone leaving low-permeability zone unswept. To improve recovery, an anionic surfactant blend (NI) was injected that altered the wettability and lowered the interfacial tension (IFT) and consequently enabled gravity and capillary pressure driven vertical counter-current flow to occur and exchange fluids between layers during a 42-day system shut-in. Cumulative recovery after a subsequent foamflood was 94.6% OOIP. The addition of lauryl betaine to NI at a weight ratio of 2:1 made the new NIB a good IFT-reducing and foaming agent with crude oil present. It showed effectiveness in water-wet homogeneous and oil-wet heterogeneous sandpacks. The unique attribute of foam with higher apparent viscosity in high- than in low-permeability regions makes it a better mobility control agent than polymer in heterogeneous systems. One single surfactant formulation such as NIB in this study that can simultaneously reduce IFT and generate foam will improve the microscopic displacement and sweep efficiency from the beginning of a chemical flooding process. Foam generation mechanisms, alkaline/surfactant processes, and foam stability in presence of crude oil were investigated in a glass micro model. Total acid number measurement with spiking method was discussed.

Thesis (Doctoral)--Universität Karlsruhe, 2001. / Abstract in German. Hochschulschrift = Thèse/Mémoire. Includes bibliographical references (p. 109-133). Also available via the World Wide Web. http://www.ubka.uni-karlsruhe.de/indexer-vvv/2002/bio-geo/1

There is a vast deposit of viscous and heavy oil, especially in Canada and Venezuela. Typically thermal methods are used to recover heavy oil. However, thermal methods are inefficient when the depth of the reservoir is high and pay thickness is low. Non-thermal methods need to be developed for viscous and heavy oils. Alkaline-surfactant-polymer (ASP) floods can be used for improving the displacement efficiency, but its effect on sweep efficiency in viscous oil recovery has not been studied. The objective of this research was to investigate 2D ASP floods in a quarter five-spot pattern. Through careful phase behavior screening, the surfactant formulation was developed that produced ultra-low interfacial tension with reservoir viscous oil (100 cp). After verifying that the design of surfactant formulation was robust and can recover more than 90% of oil in a 1D ASP sandpack flood, it was tested in a 2D geometry. Both stable and unstable tertiary ASP floods were performed in a 2D quarter five-spot sandpack using the surfactant formulation developed in 1D ASP sandpack flood. In a stable ASP quarter five-spot sandpack flood, the oil recovery was excellent (~97% of ROIP). Oil recovery in the stable 2D ASP flood behaved similar to oil recovery in the 1D stable ASP flood. However, pressure drop obtained was high which would be unsustainable in field applications. Interestingly, unstable 2D flood performed well even with an adverse mobility ratio between oil/water bank and ASP slug with a recovery of 80% ROIP. Decreasing the viscosity of ASP slug 6 times decreased the maximum pressure drop 5 times; thus, the maximum pressure drop was almost proportional to the ASP slug viscosity in a 2D pattern. This research showed that unstable ASP flood in a 2D geometry can recover significant amount of oil with a practical pressure gradient. / text

This is the first academic study of well costs and drilling times for Australia???s petroleum producing basins, both onshore and offshore. I analyse a substantial database of well times and costs sourced from government databases, industry and over 400 recent well completion reports. Three well phases are studied - Pre-Spud, Drilling and Completion. Relationships between well cost factors are considered, including phase time, phase cost, daily cost, rig day rate, well depth, basin, rig type, water depth, well direction, well objective (e.g. exploration), and type of completion (P&A or producer). Times and costs are analysed using scatter plots, frequency distributions, correlation and regression analyses. Drilling times are analysed for the period 1980 to 2004. Well time and variability in well time tend to increase exponentially with well depth. Technical Limits are defined for both onshore and offshore drilling times to indicate best performance. Well costs are analysed for the period 1996 to 2004. Well costs were relatively stable for this period. Long term increases in daily costs were offset to some extent by reductions in drilling times. Onshore regions studied include the Cooper/Eromanga, Surat/Bowen, Otway and Perth Basins. Offshore regions studied include the Carnarvon Basin shallow and deepwater, the Timor Sea and Victorian Basins. Correlations between regional well cost and well depth are usually high. Well costs are estimated based on well location, well depth, daily costs and type of completion. In 2003, the cost of exploration wells in Australia ranged from A$100,000 for shallow coal seam gas wells in the Surat/Bowen Basins to over A$50 million for the deepwater well Gnarlyknots-1 in the Great Australian Bight. Future well costs are expected to be substantially higher for some regions. This study proposes methods to index historical daily costs to future rig day rates as a means for estimating future well costs. Regional well cost models are particularly useful for the economic evaluation of CO2 storage sites which will require substantial numbers of petroleum-type wells.

Thesis (Ph.D.)--University of Adelaide, Australian School of Petroleum (ASP), 2004. / "February 2003" PhD (by publication). Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references and index.

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 216-221). Available also in a digital version from Dissertation Abstracts.