Search

In recent years, companies have employed numerous methods to lower expenses and enhance system efficiency in the oilfield. Energy consumption has constituted a significant portion of these expenses. This paper introduces a normalized consumption factor to effectively evaluate energy consumption in the oilfield. Statistical analysis has been conducted on nearly 45,000 wells from six fields in China. Critical factors such as lifting method, daily production, pump depth, gas–oil ratio (GOR), and well deviation angle were evaluated individually. Results revealed that higher production could lead to lower normalized consumption for beam pumps, progressive cavity pumps, and electric submersible pump systems, thus enhancing system efficiency. Additionally, a higher GOR might result in lower normalized consumption for the beam pump system, while the deviation angle of the well showed negligible impact on the normalized consumption factor. This manuscript offers a method to assess the impacts of artificial lift methods on production and discusses suggestions for reducing consumption associated with each lifting method in the oilfield. [ABSTRACT FROM AUTHOR]

On 7 December 2022, the State Council of China released 'Measures to Further Optimize the Implementation of the Prevention and Control of the New Coronavirus Epidemic'. The previous three-year dynamic zero epidemic prevention policy was then replaced with a full liberalization policy. On 5 May 2023, the World Health Organization declared that COVID-19 no longer constituted a 'public health emergency of international concern.' However, given the ongoing prevalence of coronavirus, emerging mutations, and the liberalization of restrictions, there are increased risks of vulnerable people contracting new variants. Low vaccination coverage among older people with compromised immune systems, puts them at further risk. The policy shift will increase pressure on already stretched health infrastructure and medical resources. This short article adds to the current debate arguing that the Chinese government should take commensurate preventive measures, including strengthening medical facilities and equipment and targeting ongoing vaccination in older people. Paper Context: The COVID-19 pandemic has disproportionately affected older people. This short paper discusses the consequences of China's liberalization policy on the older population. It suggests that the Chinese government should have taken targeted measures to mitigate health risks occurring under the changed circumstances. [ABSTRACT FROM AUTHOR]

Abstract: The Erenhot–Hegenshan suture zone is located in the eastern segment of the Central Asian Orogenic Belt (CAOB) cutting obliquely through the Da Xing’an Mountains in NE China, and represents the hotly debated boundary of the Xing’an and Songliao blocks. In this study, we present new U–Pb zircon ages and Hf isotopic compositions of zircons from Permian sandstones in the Da Xing’an Mountains (DXAM) of eastern Inner Mongolia, China. Based on the genetic relation of the suggested “Hegenshan Ocean” and the Sonidzuoqi–Xilinhot magmatic arc, we seek the eastern extension of the Erenhot–Hegenshan suture zone by tracing the provenance information of the magmatic arc from our Permian sandstones. LA-ICP-MS U–Pb dating of detrital zircons of the Permian sandstones yield evidence for two age groups of ∼280 and ∼320Ma, which represent the Late Paleozoic magmatic arcs. Zircons of the older cluster are considered to derive from the Sonidzuoqi–Xilinhot magmatic arc with its age cluster of 310–320Ma and similar ε Hf(t) values of 3.46–10.41. Further Paleozoic age groups of ∼380Ma, ∼430Ma and ∼500Ma indicate a mixture of age groups of variable origin. The samples from the central–southern DXAM comprise a mixture of Sonidzuoqi–Xilinhot and Ondon Sum–Xar Moron magmatic arcs, and even include a contribution from the magmatic arc in the northern margin of the North China craton. The samples from the central and northern DXAM contain a mixture of Sonidzuoqi–Xilinhot magmatic arc and post-orogenic magmatic rocks from the Erguna block, respectively. Synthesizing this unique information on a magmatic arc with an approximate age of 320Ma, we define a distribution of the Sonidzuoqi–Xilinhot magmatic arc as follows: the arc extends from north of Solon Obo, via Sonidzuoqi, Xilinhot through Ulanhot to Qiqihar, and then it is cut by the sinistral Nenjiang–Balihan strike-slip fault (western boundary fault of Songliao basin), and ultimately extends to Longzhen. The Erenhot–Hegenshan suture zone is located north of this magmatic arc. [Copyright &y& Elsevier]

As the west boundary fault of the Songliao Basin and the eastern margin of the Da Hinggan Mountains, the Nenjiang-Balihan fault is located in the central part of Northeast China. It is traditionally considered to be a huge deep-seated NNE-striking fault, characterized by a normal fault or detachment fault displacement. The field investigation resulted in the finding of ductile shear zones in the Lingxia and Louzidian areas, the middle and southern sectors of the fault system. The authors conducted measurements of structural elements in the field, micro-structural studies, finite strain measurements, a study on preferred crystal orientations of quartz determined by Electron Back Scatter Diffraction and muscovite Ar/Ar chronology of the deformed rocks in the ductile shear zone. The results show that the deformation features of the Lingxia and Louzidian ductile shear zones are similar, and that they represent one continuous fault, i.e., the middle-southern segment of the Nenjiang-Balihan Fault, which experienced a sinistral strike-slip ductile shearing in the Early Cretaceous (∼130 Ma). By measuring the displacement of the Xar Moron River suture and Wolegen Group on both sides of the Nenjiang-Balihan Fault, it is found that the cumulative strike-slip offset of the fault is about 40-50 km. [ABSTRACT FROM AUTHOR]

Abstract: Our new data provide evidence for the depositional age and tectonic setting of Ordovician–Devonian sandstones in the northern Da Xing''an Mountains, the eastern segment of the Central Asian Orogenic Belt (CAOB). The depositional age of the Duobaoshan Formation is younger than Middle Ordovician (462±5Ma), that of the Woduhe and Huolongmen formations is younger than Late Silurian with the youngest detrital zircon age of 417±8Ma, and 419±5Ma, respectively. The depositional age of the Niqiuhe Formation is younger than Early Silurian with the youngest detrital zircon age of 432±6Ma. All the detrital zircon ages of Ordovician–Devonian sandstones represent similar distribution characteristics in probability diagrams showing four dominant populations of ~500Ma, ~800Ma, ~1800Ma and ~2500Ma. These age groups are widely found in Devonian or pre-Devonian clastic sediments and metamorphic complexes of NE China and Mongolia. Combined with new paleomagnetic data from the Baydaric and Tuva–Mongolian composite blocks in Central Mongolia and from the Lesser Karatau block of Central Kazakhstan, and the age information from adjacent cratons and continental microplates, we suggest that the basement blocks of NE China have their origin in the Tarim craton. These basement blocks include the Erguna and Jiamusi–Khanka–Bureya blocks which rifted from the Tarim craton at ~800Ma and moved close to the Siberian craton at (or earlier than) ~500Ma with other microcontinents within the CAOB. [Copyright &y& Elsevier]

Electric Submersible Pump (ESP) is currently widely employed to help enhance production for nonlinear-flowing well with high production and high water cut well. However, ESP broken shaft is common in the oil industry. The broken shaft leads to production disruptions, resulting in significant economic losses. The objective of this paper is to evaluate Principal Component Analysis (PCA) as an unsupervised machine learning technique to detect the cause of the breakage of the ESP shaft. This method was successfully applied in the Penglai block of Bohai Oilfield in China to detect the ESP shaft fracture in real-time. A two-dimensional plot of scores of Principal Component 1 and Principal Component 2 can be used to identify different clusters of the stable region, unstable region and failure region. By this means, potential ESP shaft fracture will be found when the cluster starts deviating away from the stable region. Moreover, a PCA diagnostic model is built to predict the time at which the ESP shaft fracture occurs and to determine the main decision variable most responsible for ESP broken shaft. This paper demonstrates that the application of the PCA method performs well in monitoring the ESP operation system and predicts the impending breakage of ESP shaft with high accuracy. • ESP broken shaft is common in the oil industry, which leads to production disruptions, resulting in huge economic losses. • Principal Component Analysis is used as an unsupervised machine learning method to predict the breakage of the ESP shaft. • A plot of scores of Principal Component 1 and 2 can identify different clusters of stable, unstable and failure regions. • Once a PCA diagnostic model is built, the variable most responsible for the breakage of the ESP shaft will be determined. • By implementing T 2 and SPE equations, the PCA model has excellent accuracy in predicting the ESP shaft breakage time. • PCA can be used as an important pre-processing method and as an unsupervised machine learning technique to predict the developing ESP failures. [ABSTRACT FROM AUTHOR]

Type 1 diabetes mellitus is heterogeneous in many facets. The patients suffered from type 1 diabetes present several levels of islet function as well as variable number and type of islet-specific autoantibodies. This study was to investigate prevalence and heterogeneity of the islet autoantibodies and clinical phenotypes of type 1 diabetes mellitus; and also discussed the process of islet failure and its risk factors in Chinese type 1 diabetic patients. A total of 1,291 type 1 diabetic patients were enrolled in this study. Demographic information was collected. Laboratory tests including mixed-meal tolerance test, human leukocyte antigen alleles, hemoglobinA1c, lipids, thyroid function and islet autoantibodies were conducted. The frequency of islet-specific autoantibody in newly diagnosed T1DM patients (duration shorter than half year) was 73% in East China. According to binary logistic regressions, autoantibody positivity, longer duration and lower Body Mass Index were the risk factors of islet failure. As the disease developed, autoantibodies against glutamic acid decarboxylase declined as well as the other two autoantibodies against zinc transporter 8 and islet antigen 2. The decrease of autoantibodies was positively correlated with aggressive beta cell destruction. Autoantibodies can facilitate the identification of classic T1DM from other subtypes and predict the progression of islet failure. As there were obvious heterogeneity in autoantibodies and clinical manifestation in different phenotypes of the disease, we should take more factors into consideration when identifying type 1 diabetes mellitus.