The rapid rise of shale gas development through horizontal drilling and high volume hydraulic fracturing has expanded the extraction of hydrocarbon resources in the U.S. The rise of shale gas development has triggered an intense public debate regarding the potential environmental and human health effects from hydraulic fracturing. This paper provides a critical review of the potential risks that shale gas operations pose to water resources, with an emphasis on case studies mostly from the U.S. Four potential risks for water resources are identified: (1) the contamination of shallow aquifers with fugitive hydrocarbon gases (i.e., stray gas contamination), which can also potentially lead to the salinization of shallow groundwater through leaking natural gas wells and subsurface flow; (2) the contamination of surface water and shallow groundwater from spills, leaks, and/or the disposal of inadequately treated shale gas wastewater; (3) the accumulation of toxic and radioactive elements in soil or stream sediments near disposal or spill sites; and (4) the overextraction of water resources for high-volume hydraulic fracturing that could induce water shortages or conflicts with other water users, particularly in water-scarce areas. Analysis of published data (through January 2014) reveals evidence for stray gas contamination, surface water impacts in areas of intensive shale gas development, and the accumulation of radium isotopes in some disposal and spill sites. The direct contamination of shallow groundwater from hydraulic fracturing fluids and deep formation waters by hydraulic fracturing itself, however, remains controversial.

/pdf/a-critical-review-of-the-risks-to-water-resources-from-2v7n5hmzlz.pdf

A Critical Review of the Risks to Water Resources from Unconventional Shale Gas Development and Hydraulic Fracturing in the United States

Oil exploration and production actively began 100 years ago, from the present day. What we see now, known as primary production by natural flowing of oil by pumped wells. This covers 15% of oil recovery from reservoir. Later 25% of oil is recovered by water flooding is activated which is termed as secondary production. There is still significant oil left in the reservoir, if there is no proper employment of commercial valuable techniques for the production, the oilwell would simply be abandoned. But as the demand for oil kept raising new techniques emerged, eventually from those EOR was a successful in artificial up lifting of oil from the reservoir by providing enough pressure to the trapped oil to flow out of well. It is a tertiary production. EOR is different because it works from microscopic levels as well as by injecting the substances like gases, special liquid (polymers) and stream in the form of injection through injecting wells for oil recovery, which is termed as Enhanced Oil Recovery (EOR). The flooding in EOR, categorized as chemical flooding (by chemicals), stream or thermal injection (by stream) and miscible gas drive (CO2, N2 and LPG). These flooding will alter the physical and chemical properties of reservoirs for the flow of oil out of the well. EOR can unlock a percentage of 30-45% of trapped oil. After naming as successful technique in onshore for tertiary production, research is still going to implement EOR in offshore, to improve tertiary production and exploit hidden billion barrels of oil.

Enhanced Oil Recovery

Recent natural and man-made catastrophes, such as the Fukushima nuclear power plant, flooding caused by Hurricane Katrina, the Deepwater Horizon oil spill, the Haiti earthquake, and the mortgage derivatives crisis, have renewed interest in the concept of resilience, especially as it relates to complex systems vulnerable to multiple or cascading failures. Although the meaning of resilience is contested in different contexts, in general resilience is understood to mean the capacity to adapt to changing conditions without catastrophic loss of form or function. In the context of engineering systems, this has sometimes been interpreted as the probability that system conditions might exceed an irrevocable tipping point. However, we argue that this approach improperly conflates resilience and risk perspectives by expressing resilience exclusively in risk terms. In contrast, we describe resilience as an emergent property of what an engineering system does, rather than a static property the system has. Therefore, resilience cannot be measured at the systems scale solely from examination of component parts. Instead, resilience is better understood as the outcome of a recursive process that includes: sensing, anticipation, learning, and adaptation. In this approach, resilience analysis can be understood as differentiable from, but complementary to, risk analysis, with important implications for the adaptive management of complex, coupled engineering systems. Management of the 2011 flooding in the Mississippi River Basin is discussed as an example of the successes and challenges of resilience-based management of complex natural systems that have been extensively altered by engineered structures.

Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems

https://www.elsevier.com/__data/assets/pdf_file/0019/97012/Oil-and-gas-wells-and-their-integrity.pdf

Oil and gas wells and their integrity : implications for shale and unconventional resource exploitation

Application of machine learning and artificial intelligence in oil and gas industry

Using Fatigue-Failure Envelope for Cement-Sheath-Integrity Evaluation


 Drilling problems such as stick slip vibration/hole cleaning, pipe failures, loss of circulation, BHA whirl, stuck pipe incidents, excessive torque and drag, low ROP, bit wear, formation damage and borehole instability, and the drilling of highly tortuous wells have only been tackled using physics-based models. Despite the mammoth generation of real-time metadata, there is a tremendous gap between statistical based models and empirical, mathematical, and physical-based models. Data mining techniques have made prominent contributions across a broad spectrum of industries. Its value is widely appreciated in a variety of applications, but its potential has not been fully tapped in the oil and gas industry. This paper presents a review compiling several years of Data Analytics applications in the drilling operations. This review discusses the benefits, deficiencies of the present practices, challenges, and novel applications under development to overcome industry deficiencies. This study encompasses a comprehensive compilation of data mining algorithms and industry applications from a predictive analytics standpoint using supervised and unsupervised advanced analytics algorithms to identify hidden patterns and help mitigate drilling challenges.
 Traditional data preparation and analysis methods are not sufficiently capable of rapid information extraction and clear visualization of big complicated data sets. Due to the petroleum industry's unfulfilled demand, Machine Learning (ML)-assisted industry workflow in the fields of drilling optimization and real time parameter analysis and mitigation is presented.
 This paper summarizes data analytics case studies, workflows, and lessons learnt that would allow field personnel, engineers, and management to quickly interpret trends, detect failure patterns in operations, diagnose problems, and execute remedial actions to monitor and safeguard operations. The presence of such a comprehensive workflow can minimize tool failure, save millions in replacement costs and maintenance, NPV, lost production, minimize industry bias, and drive intelligent business decisions. This study will identify areas of improvement and opportunities to mitigate malpractices. Data exploitation via the proposed platform is based on well-established ML and data mining algorithms in computer sciences and statistical literature. This approach enables safe operations and handling of extremely large data bases, hence, facilitating tough decision-making processes.

The Role of Machine Learning in Drilling Operations; A Review

Low cycle cement fatigue experimental study and the effect on HPHT well integrity

Estimation of Casing-Cement-Formation Interaction using a new analythical model

Detecting and Modeling Cement Failure in High Pressure/High Temperature Wells Using Finite-Element Method. (December 2005) Mehdi Abbaszadeh Shahri, B.S., Petroleum University of Technology, Iran Chair of Advisory Committee: Dr. Jerome. J. Schubert A successful cement job results in complete zonal isolation while saving time and money. To achieve these goals, various factors such as well security, casing centralization, effective mud removal, and gas migration must be considered in the design. In the event that high-pressure and high-temperature (HPHT) conditions are encountered, we must attempt to achieve permeability in the set cement to prevent gas migration and to prevent any other fluid passing through to collapse the entire structure. Therefore, the design of the cement must be such that it prevents: • Micro-annuli formation • Stress cracking • Corrosive fluid invasion • Fluid migration • Annular gas pressure In HPHT cases, we need more flexible cement than in conventional wells. This cement expands more at least 2 to 3 times more in some special cases. The stress in the cement is strongly connected with temperature and pressure, as well as lithology and in-situ stress. If we can define a method which connects the higher temperature to the lower stress field, we would have the solution for one side of the equation, and then we could model the pressure (stress principles) at the designated depth and lithology. Since the stress is so dependent on temperature, the temperature variation must be accurately predicted to properly design the fluid and eliminate excessive time spent waiting on cement. In addition, a post-job analysis is necessary to ascertain zonal isolation and avoid unnecessary remedial work.

http://oaktrust.library.tamu.edu/bitstream/handle/1969.1/3241/etd-tamu-2005C-PETE-shahri.pdf

Detecting and Modeling Cement Failure in High-Pressure/High-Temperature (HP/HT) Wells, Using Finite Element Method (FEM)

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