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Glauconite develops widely in T Member in Oriente Basin, Ecuador. The presence of Galuconite reveals the information that can help to determine the sediment environment. However, the distribution of glauconite also makes the pay zone identification of glauconitic sandstone difficult in oilfield operation in many ways. Detailed core data analysis of glauconitic sandstone, include core description, thin section observation, porosity and water saturation, has been performed. The core data indicates that sediment environment changed from coastal estuary to open shelf during the deposition of T Member. The PEF and RHOB data from conventional well logs have been selected to estimate the concentration of glauconite based on the correlation with observation of thin section of core. And porosity estimation can be improved by using various matrix density with consideration of concentration of glauconite, which shows better result than using regular uniform matrix density by comparison with core data. Further, water saturation of glauconitic sandstone can be improved. And gas log data from mud logging has been introduced in pay zone identification of glauconitic sandstone. The combination analysis of well log data and gas log data can improve the determination of pay zone of glauconitic sandstone. The practice in oilfield proves the effectiveness of this method.

Piping robots are needed for inner pipe operations in nuclear and oil & gas industries etc. Many pipe inspection robots have been developed. However the payload of these robots is small. To perform heavy duty operations such as grinding, piping robot with large payload must be developed. Furthermore detailed payload analysis which is important for the piping robot design is not available.

Prediction of lithology distribution is critical for development of oilfield and is also one of the basic tasks of geological modeling. Stochastic simulation has been proved to be an effective method for simulation the distribution of lithology. While stochastic simulation technique is theoretically a mathematical method, the result of simulation will be strongly affected by many factors, such as the quantity, quality, and distribution of well data, and so on. In the area or oilfield with limited wells and insufficient data, the uncertainty of simulation result will be very high, and the reliability of the result will be very low. This result with high uncertainty and low reliability will lead to very poor prediction of sand and shale. Further, the reliability of the result of petrophysical modeling will be low. This article introduces a new method by using constraint condition with high quality to improve the simulation result of lithology distribution and decrease the uncertainty of simulation result. Stratigraphic forward modeling is an effective approach to simulate the process of deposition, and this approach can characterize the geometry and distribution of complex sedimentation. But the resolution of the simulation result of this approach is lower than the requirement of development stage of oilfield. Seismic inversion has been proved to be an effective way with high resolution to describe the distribution of lithology by using high-quality seismic data, while seismic inversion is difficult to reflect the geological process and pattern. The combination of these two methods can provide good constraint condition for stochastic simulation. By using the results of stratigraphic forward modeling and seismic inversion, we can build the trend models for different lithology. The trend models can be used in stochastic simulation, and the trend models can improve the result of stochastic simulation. This paper took A oilfield in Oriente Basin in Ecuador as an example to show the process of this method. We built the stratigraphic forward modeling model based on the geological understanding and completed the research of seismic inversion of M1 layer of Napo Formation. The result of serigraphic forward modeling and seismic inversion was resampled into the geological model. Based on these two results, the trend models of sand and shale of M1 layer have been completed. The trend models have been used to constrain the stochastic simulation of lithology with sequential indicator simulation algorithm. This method can effectively decrease the uncertainty of simulation result caused by insufficient well data and improve the reliability of lithological model which further improves the result of petrophysical modeling.

It is challenging to inspect a metal part with textures because the conventional defect detection methods cannot effectively distinguish between texture features and defect features, which can easily lead to misjudgment of defects. In this paper, we propose a new method for detecting surface defects which can effectively eliminate the texture features' impact on defect detection. By computing the average energy of directional length and average gray scale energy, the distribution of the energy difference in the whole image is obtained. According to the distribution of the energy difference, textures' impact on defects detection can be effectively removed and the surface defects can then be extracted. Experiments were performed to validate the proposed method and the results demonstrate the proposed method can effectively remove surface textures and accurately detect surface defects.

To avoid violent shaking in high-speed material handling, material handling robot must keep its velocity curve smooth during its motion. In order to meet these requirements, we propose a linear trajectory planning method and applied this method on a high-speed material handling robot with three joints. In this method, we firstly develop a piecewise cubic function based on continuous acceleration to generate robot tool trajectory. By setting the segmentation time and calculating corresponding coordinate position, the robot can perform continuous motion. At last we did simulation using Matlab and performed practical test on the material handling robot. Both results showed that this planning method can meet the material handling requirements with high speed and smooth movement.

Stochastic simulation of lithology is critical in geological modeling, and the result quality relies on the well data analysis. The traditional method may involve too many uncertainties due to the limited wells. This paper introduces a new method to improve the simulation of lithology distribution of tide-dominated estuary using probability volume generated by stratigraphic forward modeling as key input for trend model. Based on the core analysis and investigation on regional geology, the stratigraphic forward modeling approach generates an initial model by using the sequence stratigraphic scheme. And the sensitivity analysis provides an indication of adjusting the influencing parameters which control the sand and shale distribution. The models will be compared with the well data, geological concept, and seismic attribute. The selected model will be resampled into geological grid to generate the trend volume combined with seismic inversion data. Further, the lithology distribution can be simulated by using stochastic method with the trend volume. This approach has been successfully applied in JE-AW oil field to improve the geological model of M1. Typical tidal sedimentary structures, such as mud drapes, and wavy bedding shown in core and overall upward fining shown in logs, reveal the tide-dominated estuary environment during the deposition of M1. Three sub-zones (layers) of M1 are identified and correlated. Based on the sensitivity analysis, the sediment input and subsidence is adjusted for reliable stratigraphic forward modeling. The trend model is generated by inputting the result from stratigraphic forward modeling and seismic inversion. Finally, the lithology distribution is simulated using the trend model. This method improves the lithology stochastic simulation of tide-dominated estuary honoring the well and seismic data. This method reduces the uncertainties of stochastic modeling caused by limited wells and improves the predictability of lithology model.

Object recognition and grasping plays a key role in robotic systems, especially for the autonomous robots to implement object sorting tasks in a warehouse. In this paper, we present a global texture-shape 3D feature descriptor which can be utilized in a system of object recognition and grasping, and can perform object sorting tasks well. Our proposed descriptor stems from the clustered viewpoint feature histogram (CVFH), which relies on the geometrical information of the whole 3D object surface only, and can not perform well in recognizing the objects with similar geometrical information. Therefore, we extend the CVFH descriptor with texture and color information to generate a new global 3D feature descriptor. The proposed descriptor is evaluated in tasks of recognizing and classifying 3D objects by applying multi-class support vector machines (SVM) in both public 3D image dataset and real scenes. The results of evaluation show that the proposed descriptor achieves a significant better performance for object recognition compared with the original CVFH. Then, the proposed descriptor is applied in our object recognition and grasping system, showing that the proposed descriptor helps the system implement the object recognition, object grasping and object sorting tasks well.

A novel C25 sterol peroxide, phomasterol A (1), together with two known compounds (2–3), was isolated from the endophytic fungus Phoma sp. EA-122. The structure of phomasterol A (1) was elucidated by MS, 1D, and 2D NMR data analyses. Phomasterol A (1) was evaluated for its inhibitory activities against protein-tyrosine phosphatases MEG2 and PTP1Bc, showing moderate activities with identical IC50 values of 25 μM.

In this study, numerical simulation of anchor bolt pullout in plain concrete by a heterogeneous numerical model is presented. The heterogeneity of the concrete material was modeled by randomly assigning strength and elastic modulus to the elements according to Weibull's distribution. The ongoing debonding process was obtained, including crack initiation, crack propagation and formation of the concrete cone. The numerical results indicate that there is a strong size effect on failure resistance of the concrete cone. By increasing the anchor head size, peak pullout load and the volume of concrete cone increase. The peak pullout load and the volume of concrete cone also increase with the increasing of embedded length. With this heterogeneous numerical model, the asymmetrical crack patterns and the crack branching observed in tests is obtained. Moreover, asymmetrical crack and crack branching were easy to occur with lower homogeneity index. The numerical results agreed well with the experimental investigations.

Abstract With the annual growth of development scale and production, the research of heavy oil and oil sands become more and more important. Due to the characteristics of heavy oil and oil sands, the degree of reserves recovery is restricted by development mode. So there is a big difference in classification criterions and evaluation techniques of reserves in the world. In this paper, using the major heavy oil and oil sands accumulation areas —Venezuela heavy oil belt and Canada oil sands as example, we analyse the reservoir characteristic of heavy oil and oil sands, and then discuss the classification and evaluation techniques of reserves suitable for different development modes. The heavy oil belt in Venezuela and oil sands in Canada are all characterized by huge thickness, middle-fine sandstone, loose cementation, high porosity and high permeability. To adapt different development mode, we establish corresponding evaluation criterions for reservoir, including porosity, permeability, shale content, saturation, barrier and interbed, the thickness and width of continuous oil layer and so on. We classify the reserves as OOIP, economic reserves, reserves for horizontal well, reserves for steam flooding (SF)/ cyclic steam stimulation (CSS) and reserves for SAGD. Using logging and geophysical techniques, we evaluate and classify the reserves. 1.Introduction Heavy oil and oil sands are characterized by shallow buried depth, large thickness, huge reserves and unconsolidated structures. Because crude oil has high viscosity, conventional vertical wells generally have no or extremely low productivity. Currently, these reservoirs are predominantly developed by horizontal wells in two stages: cold production and thermal production. All these conditions have presented new requirements on contents and methods of reserve evaluation. In this essay, through study on reservoir features and corresponding development techniques for heavy oil in Venezuela and oil sands in Canada, we put forward reserve assessment methods and techniques by class for various development modes. 2.Reservoir evaluation and selection criteria for heavy oil and oil sands development Currently, cold production (CP) is the prevailing development method adopted for heavy oil in Venezuela, at the same time, cyclic steam stimulation (CSS), steam flooding (SF) and SAGD have been tested. Oil sands in Canada are mostly developed by SAGD and open mining. A series of reservoir selection criteria have been proposed to cope with requirements of different development methods with horizontal wells on oil layers (Table 1).

In modern industries, the lack of accurate real-time energy monitoring will lead to energy waste. To address this issue, we propose an effective, reliable and low-cost solution. Our scheme uses XBee-Pro S2 for communications, and provides user-friendly application software based on WPF and controls of NetAdvantage. The application of high performance XBee-Pro S2 modules solves the defects of the traditional ZigBee networks with short transmission distance and week anti-jamming ability. The WPF framework employed in this work leads to enhancement on the UI, the development efficiency, and the reliability of the monitoring software. System testing shows that the operation of the network is stable and the transmission of data is reliable.

This thesis describes the development and implementation of robust impedance control to perform an assembly task of inserting a printed circuit board (PCB) into an edge connector socket using a multi-joint robot. The insertion task involves compliant manipulation in which a substantial force is needed to accomplish the insertion operation. Due to dynamic constraints from the environment, this task is quite demanding and is adopted in the research as a common test-bed to evaluate the performance of robust control schemes with those of model-based control laws. The purpose is to identify an effective control technique for this application and hope that the findings can be extended to other assembly tasks of similar nature. Master of Engineering