A new method for clastic reservoir prediction based on numerical simulation of diagenesis: A case study of Ed1 sandstones in Bozhong depression, Bohai Bay Basin, China

The use of seismic exploration technique to provide reliable reservoir information is a conventional method. However, due to its quality and resolution reasons, it cannot satisfy the detailed research and characterization of reservoirs, especially the clastic reservoir with thin sand body. Diagenesis is a fundamental process in the development and formation of all petroleum reservoirs and is a major contributor to their ultimate physical properties. Based on numerical simulation of diagenesis, a new prediction method called geology prediction techniques is presented to simulate the evolution of the diagenetic stages, diagenetic facies and porosity of clastic reservoirs and ultimately for favorable reservoir prediction. It emphasizes the idea of dynamic quantitative research dominated by process recovery, the most important of which is the establishment of mathematical models, including mineral dissolution models, mineral cementation models and sediment compaction models using the experimental data in study area and the results of previous studies. The essence of this method is illustrated, and its effectiveness is proved using Ed1 clastic sandstones in the Bozhong depression, Bohai Bay Basin, China. At present, the reservoir is in the early diagenetic stage B (IB) and the middle diagenetic stage A1 (IIA1). The major diagenetic processes that influence the porosity of the sandstones in study area are mechanical compaction, carbonate cementation, quartz cementation, clay cementation, feldspar dissolution and carbonate dissolution. There are three types of sandstones including fine sandstone, siltstone, and argillaceous siltstone, and the variation range of primary porosity of these sandstones is from 26% to 38%. Compaction and carbonate cementation are the main reasons for porosity reduction, with porosity loss percentage by compaction (P-Com) and porosity loss percentage by cementation of carbonate (P-C-Car) being 53.1% ~ 7.8% (av. 41.9%) and 53.1% ~ 7.8% (av. 18%), respectively, while carbonate dissolution and feldspar dissolution can greatly improve reservoir physical property, with porosity increase percentage by dissolution of carbonate (P-D-Car) and porosity increase percentage by dissolution of feldspar (P-D-Fel) being 0 ~ 9.9% (av. 8.9%) and 0 ~ 27.8% (av. 9.4%), respectively. The predicted porosities match the measured porosities well.Cited as: Qian, W., Yin, T., Hou, G. A new method for clastic reservoir prediction based on numerical simulation of diagenesis: A case study of the Ed1 clastic sandstones in the Bozhong depression, Bohai Bay Basin, China. Advances in Geo-Energy Research, 2019, 3(1): 82-93, doi: 10.26804/ager.2019.01.0

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A new method for clastic reservoir prediction based on numerical simulation of diagenesis: A case study of Ed1 sandstones in Bozhong depression, Bohai Bay Basin, China

The use of seismic exploration technique to provide reliable reservoir information is a conventional method. However, due to its quality and resolution reasons, it cannot satisfy the detailed research and characterization of reservoirs, especially the clastic reservoir with thin sand body. Diagenesis is a fundamental process in the development and formation of all petroleum reservoirs and is a major contributor to their ultimate physical properties. Based on numerical simulation of diagenesis, a new prediction method called geology prediction techniques is presented to simulate the evolution of the diagenetic stages, diagenetic facies and porosity of clastic reservoirs and ultimately for favorable reservoir prediction. It emphasizes the idea of dynamic quantitative research dominated by process recovery, the most important of which is the establishment of mathematical models, including mineral dissolution models, mineral cementation models and sediment compaction models using the experimental data in study area and the results of previous studies. The essence of this method is illustrated, and its effectiveness is proved using Ed1 clastic sandstones in the Bozhong depression, Bohai Bay Basin, China. At present, the reservoir is in the early diagenetic stage B (IB) and the middle diagenetic stage A1 (IIA1). The major diagenetic processes that influence the porosity of the sandstones in study area are mechanical compaction, carbonate cementation, quartz cementation, clay cementation, feldspar dissolution and carbonate dissolution. There are three types of sandstones including fine sandstone, siltstone, and argillaceous siltstone, and the variation range of primary porosity of these sandstones is from 26% to 38%. Compaction and carbonate cementation are the main reasons for porosity reduction, with porosity loss percentage by compaction (P-Com) and porosity loss percentage by cementation of carbonate (P-C-Car) being 53.1% ~ 7.8% (av. 41.9%) and 53.1% ~ 7.8% (av. 18%), respectively, while carbonate dissolution and feldspar dissolution can greatly improve reservoir physical property, with porosity increase percentage by dissolution of carbonate (P-D-Car) and porosity increase percentage by dissolution of feldspar (P-D-Fel) being 0 ~ 9.9% (av. 8.9%) and 0 ~ 27.8% (av. 9.4%), respectively. The predicted porosities match the measured porosities well

Left-Invariant PID Control Almost Globally Stabilizes Rigid-Body Attitudes with Right-Invariant Biases

This paper studies the robust stabilization of rigid-body attitudes represented by a special orthogonal matrix. A geometric proportional–integral–derivative (PID) controller is proposed with all the input commands defined in the dual space so*(3) of a Lie algebra for left-invariant systems evolving on a Lie group SO(3). Almost global asymptotic stability (AGAS) of the close system is proved by constructing a gradient-descent Lyapunov function after explicitly performing two stages of variable change. The attitudes are stabilized to the stable equilibrium despite the influence of inertially fixed biases. The convergent behaviors and the robustness to biases are verified by numerical simulations

Diagnosis and Treatment of Multiple Primary Lung Cancer

Multiple primary lung cancer (MPLC) is an uncommon entity of the primary lung cancer. With the widespread use of early detection tools such as multislice spiral computed tomography (CT), positron emission tomography (PET), and the better survival results after resection of primary lung cancer, more and more MPLC have been detected. However, the current diagnostic and therapeutic methods cannot meet the needs of MPLC individualized demand of diagnosis and treatment. At present, diagnostic criteria of MPLC are based on histological types, genetic characteristics, image features, tumor locations and clinical manifestation. On the treatment of MPLC, Surgery-based multi-discipline comprehensive treatment is regarded as the treatment of choice. In this paper, we make a review through summarizing the latest literature progress on the epidemiology, etiology, diagnostic criteria, treatment options and prognosis of MPLC

Detection of Particulate Matter Changes Caused by 2020 California Wildfires Based on GNSS and Radiosonde Station

From August to October 2020, a serious wildfire occurred in California, USA, which produced a large number of particulate matter and harmful gases, resulting in huge economic losses and environmental pollution. Particulate matter delays the GNSS signal, which affects the like precipitable water vapor (LPWV) derived by the GNSS non-hydrostatic delay. Most of the information of GNSS-derived LPWV is caused by water vapor, and a small part of the information is caused by particulate matter. A new method based on the difference (ΔPWV) between the PWV of virtual radiosonde stations network and GNSS-derived LPWV is proposed to detect the changes of particulate matter in the atmosphere during the 2020 California wildfires. There are few radiosonde stations in the experimental area and they are far away from the GNSS station. In order to solve this problem, we propose to use the multilayer perceptron (MLP) neural network method to establish the virtual radiosonde network in the experimental area. The PWV derived by the fifth-generation European center for medium-range weather forecasts reanalysis model (PWVERA5) is used as the input data of machine learning. The PWV derived by radiosonde data (PWVRAD) is used as the training target data of machine learning. The ΔPWV is obtained based on PWV derived by the virtual radiosonde station network and GNSS in the experimental area. In order to further reduce the influence of noise and other factors on ΔPWV, this paper attempts to decompose ΔPWV time series by using the singular spectrum analysis method, and obtain its principal components, subsequently, analyzing the relationship between the principal components of ΔPWV with particulate matter. The results indicate that the accuracy of PWV predicted by the virtual radiosonde network is significantly better than the fifth-generation European center for the medium-range weather forecast reanalysis model, and the change trend of ΔPWV is basically consistent with the change law of particulate matter in which the value of ΔPWV in the case of fire is significantly higher than that before and after the fire. The mean of correlation coefficients between ΔPWV and PM10 at each GNSS station before, during and after wildfires are 0.068, 0.397 and 0.065, respectively, which show the evident enhancement of the correlation between ΔPWV and particulate matter during wildfires. It is concluded that because of the high sensitiveness of ΔPWV to the change of particulate matter, the GNSS technique can be used as an effective new approach to detect the change of particulate matter and, then, to detect wildfires effectively

Mucoepidermoid Carcinoma of the Lung: Report of 29 Cases

Background and objective Pulmonary mucoepidermoid carcinoma (MEC) is an extremely rare pulmonary malignant tumor, its clinical features and conditions of prognosis is not entirely clear. The aim of this study is to discuss clinical features, diagnostic and therapeutic methods, and prognosis of pulmonary MEC. Methods We retrospectively studied 29 pulmonary MEC patients who diagnosed from January 2006 to December 2015 in Affiliated Hospital of Zhengzhou University. The clinical features, prognosis, diagnostic and therapeutic methods were analyzed. Results There were 20 patients identified as pulmonary MEC, which constitutes 0.18% of all the lung tumor patients. There were 18 males and 11 females, the median age of the patients was 45 years (range 10-79). There were 17 patients identified as high-grade pulmonary MEC and 12 low-grade. Epidermal growth factor receptor (EGFR) mutation detection was performed in six patients, none was positive. 17 cases was underwent surgery based comprehensive treatment, 12 cases non-operatived treatment. The median follow-up time was 35 (5-114) months in this cohort of 29 patients. During the follow up, incidence of death was found in 17 cases. The overall 1-, 3-, 5-year survival rates were 65.5%, 51.2%, 39.4%, respectively. The median survival time was 37 months. Conclusion The incidence of pulmonary MEC is low, lacking specific clinical characterization. The diagnosis mainly depends on postoperative pathology, aided by immunohistochemical. Surgery is the main treatment method. The majority of pathology was high-grade type. The prognosis of pulmonary MEC closely relates to the pathological types and clinical stage. EGFR-tyrosine kinase inhibitor (EGFR-TKI) is expected to improve the prognosis of pulmonary MEC