Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and anomalous rock faces. Furthermore, the paper explores the adoption of advanced methods, including hydraulic flow units (HFU), providing a fine-grained understanding of reservoir heterogeneity and contributing to the prediction of flow dynamics. The final section includes structural geological models, petrophysical data collected, rock type classification, and spatial data to better represent the reservoir bottom structure. It provides a valuable resource for researchers, geologists, and engineers seeking to characterize reservoirs and make optimal decisions on hydrocarbon exploration and production. It is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling.
Wastewater recycling for non-potable uses has gained significant attention to mitigate the high pressure on freshwater resources. This requires using a sustainable technique to treat natural municipal wastewater as an alternative to conventional methods, especially in arid and semi-arid rural areas. One of the promising techniques applied to satisfy the objective of wastewater reuse is the constructed wetlands (CWs) which have been used extensively in most countries worldwide through the last decades. The present study introduces a significant review of the definition, classification, and components of CWs, identifying the mechanisms controlling the removal process within such units. Vertical, horizontal, and hybrid CWs
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Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia
... Show MoreThis research paper aimed to quantitively characterize the pore structure of shale reservoirs. Six samples of Silurian shale from the Ahnet basin were selected for nitrogen adsorption-desorption analysis. Experimental findings showed that all the samples are mainly composed of mesopores with slit-like shaped pores, as well as the Barrett-Joyner-Halenda pore volume ranging from 0.014 to 0.046 cm3/ 100 g, where the lowest value has recorded in the AHTT-1 sample, whereas the highest one in AHTT-6, while the rest samples (AHTT-2, AHTT-3, AHTT-4, AHTT-5) have a similar average value of 0.03 cm3/ 100 g. Meanwhile, the surface area and pore size distribution were in the range of 3.8 to 11.1 m2 / g and 1.7 to 40 nm, respectively.
... Show MoreThe paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
... Show MoreIn addition to the primary treatment, biological treatment is used to reduce inorganic and organic components in the wastewater. The separation of biomass from treated wastewater is usually important to meet the effluent disposal requirements, so the MBBR system has been one of the most important modern technologies that use plastic tankers to transport biomass with wastewater, which works in pure biofilm, at low concentrations of suspended solids. However, biological treatment has been developed using the active sludge mixing process with MBBR. Turbo4bio was established as a sustainable and cost-effective solution for wastewater treatment plants in the early 1990s and ran on minimal sludge, and is easy to maintain. This
... Show MoreThe heterogeneity nature of carbonate reservoirs shows sever scattering of the data, therefore, one has to be cautious in using the permeability- porosity correlation for calculating permeability unless a good correlation coefficient is available. In addition, a permeability- porosity correlation technique is not enough by itself since simulation studies also require more accurate tools for reservoir description and diagnosis of flow and non-flow units. Evaluation of reservoir characterization was conducted by this paper for Mishrif Formation in south Iraqi oil field (heterogeneous carbonate reservoir), namely the permeability-porosity correlation, the hydraulic units (HU’s) and global hydraulic elements (GHE
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