Chromatography and Spectrometry in Food Safety and Pharmaceutical Analysis.

With the acceleration
of global industrialization, the mounting
pressure from growing global energy demand has emerged as a critical
challenge and crisis worldwide. Deep, ultradeep and unconventional
oil and gas resources play an increasingly pivotal role in enhancing
reserve and production growth. As a core link in the
field of oil and gas exploitation, safe and efficient drilling operations
are critical to ensuring the cost-effective development of oil and
gas resources. However, the drilling of
deep formations usually faces complex geological conditions including
abnormally high formation temperature and pressure, narrow safe density
window and well-developed natural fractures. When annular pressure
exceeds the formation leakage pressure, formation breakdown occurs,
which will lead to drilling fluid lost circulation. According
to the difference in leakage rate and flow channel, lost circulation
can be classified into minor leakage, moderate leakage and severe
leakage. Vertically, if multiple sets
of pressure systems exist in the formation and the wellbore structure
is unreasonably designed, the simultaneous occurrence of multiple
leakage points may take place. Existing studies have shown that nearly
a quarter of oil wells worldwide have experienced varying degrees
of lost circulation during drilling operations, which severely hinders
the cost-effective development of oil and gas resources. In addition, drilling fluid lost circulation
will not only cause formation damage, but also prolong the drilling
cycle, even lead to well abandonment and huge economic losses. Therefore, accurate localization of thief zone locations is of great
significance for realizing safe, efficient and economic drilling operations. After decades of development, lost circulation detection technologies
have formed three mainstream systems, namely conventional detection,
geomechanical analysis, and intelligent detection. However, all types
of methods have notable limitations and are difficult to adapt to
complex drilling conditions. Among these systems,
conventional detection methods can be further divided into manual
monitoring methods and instrument-based testing methods. The direct
observation method, a core manual monitoring approach, identifies
the occurrence of lost circulation by monitoring mud pit liquid level
variations, flow fluctuations and mud logging data. This method relies
on manual empirical judgment, with strong subjectivity and lagged
response. It can only roughly identify the trend of lost circulation,
and cannot provide accurate information on thief zone locations. Instrument-based testing methods mainly adopt
professional testing equipment including electronic flowmeters, temperature
measuring instruments and pressure measuring instruments. The dynamic
changes of downhole flow, temperature, pressure and other parameters
are monitored in real time via sensors. Combined with on-site drilling
conditions, the measured data are used to realize the localization
of downhole lost circulation positions. Pressure While
Drilling (PWD) tools can collect downhole pressure data in real time,
but are prone to failure under high temperature and high pressure
environments. They also have high application costs and are difficult
to promote on a large scale. The temperature
measurement method focuses on measuring the annular temperature distribution,
and identifies thief zones through abnormal temperature gradients.
However, the complex downhole environment may affect the testing accuracy
and lead to misjudgment. The geomechanical
analysis method is based on principles. It comprehensively evaluates
wellbore stability and drilling fluid lost circulation risk through
characterizing formation fracture parameters, analyzing in situ stress
states, and conducting rock mechanics tests. Although this method can realize advance prediction of lost circulation
in the target work area without professional testing equipment for
downhole environment measurement, its high-precision prediction requires
a large number of high-quality rock mechanics tests, well logging
data and seismic data to invert geological conditions including the
rock mechanics profile of the target drilling block. These data are
difficult to obtain and have high acquisition costs, requiring a large
amount of preliminary work. In addition, the derivation process of
the required calculation models is relatively complex. Different models
are applicable to different geological conditions, which leads to
certain limitations of this method. Its prediction accuracy is also
affected by the geological conditions of the target drilling block. With continuous technological breakthroughs and iterations in the
field of artificial intelligence, its application in oil and gas engineering
has been increasingly popularized, and artificial intelligence-based
lost circulation detection methods have been gradually developed. Artificial intelligence-based detection methods
construct algorithm mod