ABSTRACT In dam construction stages when an earth embankment has retained a reservoir with constant water surface elevation for a long time, seepage conditions within the embankment will be reach a steady state. If it is necessary to drain the reservoir quickly, the pore-water pressures in the embankment may remain relatively high while the stabling effect of the reservoir's weight along the upstream (U/S) side for the embankment has removed. This process is referring to as "Rapid Drawdown" and may be cause instability in the upstream (U/S) face of the embankment. Kongele dam is one of the proposed earth dams to be implement within the current plan in Iraq. The authors study pore water pressure and the effect of rapid drawdown for the dam d

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ rates

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

The main aim of this paper is studied the punching shear and behavior of reinforced concrete slabs exposed to fires, the possibility of punching shear failure occurred as a result of the fires and their inability to withstand the loads. Simulation by finite element analysis is made to predict the type of failure, distribution temperature through the thickness of the slabs, deformation and punching strength. Nonlinear finite element transient thermal-structural analysis at fire conditions are analyzed by ANSYS package. The validity of the modeling is performed for the mechanical and thermal properties of materials from earlier works from literature to decrea

A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

The invention relates to a coordinate measuring machine (CMM) for determining a measuring position of a probe. The AACMM isdepends on the robotkinematics (forward and reverse) in their measurementprinciple, i.e., using the AACMM links and joint angles todetermine the exact workspace or part coordinates. Hence, themeasurements are obtained using an AACMM will be extremely accurate and precise since that ismerely dependent on rigid structural parameters and the only source of measurement error is due to human operators. In this paper, a new AACMM design was proposed. The new AACMM design addresses common issues such as solving the complex kinematics, overcoming the workspace limitation, avoiding singularity, and eliminating the effects of