The main role of infill drilling is either adding incremental reserves to the already existing one by intersecting newly undrained (virgin) regions or accelerating the production from currently depleted areas. Accelerating reserves from increasing drainage in tight formations can be beneficial considering the time value of money and the cost of additional wells. However, the maximum benefit can be realized when infill wells produce mostly incremental recoveries (recoveries from virgin formations). Therefore, the prediction of incremental and accelerated recovery is crucial in field development planning as it helps in the optimization of infill wells with the assurance of long-term economic sustainability of the project. Several approaches are presented in literatures to determine incremental and acceleration recovery and areas for infill drilling. However, the majority of these methods require huge and expensive data; and very time-consuming simulation studies. In this study, two qualitative techniques are proposed for the estimation of incremental and accelerated recovery based upon readily available production data. In the first technique, acceleration and incremental recovery, and thus infill drilling, are predicted from the trend of the cumulative production (Gp) versus square root time function. This approach is more applicable for tight formations considering the long period of transient linear flow. The second technique is based on multi-well Blasingame type curves analysis. This technique appears to best be applied when the production of parent wells reaches the boundary dominated flow (BDF) region before the production start of the successive infill wells. These techniques are important in field development planning as the flow regimes in tight formations change gradually from transient flow (early times) to BDF (late times) as the production continues. Despite different approaches/methods, the field case studies demonstrate that the accurate framework for strategic well planning including prediction of optimum well location is very critical, especially for the realization of the commercial benefit (i.e., increasing and accelerating of reserve or assets) from infilled drilling campaign. Also, the proposed framework and findings of this study provide new insight into infilled drilling campaigns including the importance of better evaluation of infill drilling performance in tight formations, which eventually assist on informed decisions process regarding future development plans.
An experimental study was carried out to improve the surface roughness quality of the stainless steel 420 using magnetic abrasive finishing method (MAF). Four independent operation parameters were studied (working gap, coil current, feed rate, and table stroke), and their effects on the MAF process were introduced. A rotating coil electromagnet was designed and implemented to use with plane surfaces. The magnetic abrasive powder used was formed from 33%Fe and 67% Quartz of (250µm mesh size). The lubricant type SAE 20W was used as a binder for the powder contents. Taguchi method was used for designing the experiments and the optimal values of the selected parameters were found. An empirical equation representing the r
... Show MoreA second-order sliding mode control is used for high-order uncertain plants using equivalent control approach to improve the performance of control systems. They combine backstepping with quasi-continuous controller and twisting controllers. This paper considers a two of the most popular controllers that are used to solve the nonlinearities problem which are the backstepping quasi-continuous control (BQCC) and backstepping twisting controllers to control the angular velocity of a hydraulic motor to improve tracking performance and robustness to uncertainties. For the system dynamics, a linear state feedback with suitable high gain was designed as the virtual controller, where steady state error can be made arbitrarily small according to the
... Show MoreSteel–concrete–steel (SCS) structural systems have economic and structural advantages over traditional reinforced concrete; thus, they have been widely used. The performance of concrete made from recycled rubber aggregate from scrap tires has been evaluated since the early 1990s. The use of rubberized concrete in structural construction remains necessary because of its high impact resistance, increases ductility, and produces a lightweight concrete; therefore, it adds such important properties to SCS members. In this research, the use of different concrete core materials in SCS was examined. Twelve SCS specimens were subjected to push-out monotonic loading for inspecting their mechanical performance. One specimen was constructed from co
... Show MoreAn inert matrix that is used to control the release of (PTX) was prepared using Eudragit RL100 and RSPM types as matrix forming agent . The matrices were prepared by either dry granulation(slugging) , or wet granulation method using chloroform as a solvent evaporation vehichle. The cumulative release was adjusted by using polyvinylpyrollidone (PVP) or ethylcellulose (EC) polymers .The results indicated that both methods of preparation were valid for incorporation PTX as a sustained release granules .Moreover ,the results revealed that best polymer used was Eudragit RSPM in 3:20 polymer drug ratio .Besides to that , the results indicated that the release profiles were affected by pH- medium&
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreThe steady state performance of the counter rotating floating ring Journal bearing is analyzed with isothermal finite bearing theory. The effect of different parameters affecting the performance of the bearing (namely speed ratio, clearance ratio and radii ratio), have been investigated. The load carrying capacity of the bearing increasing with decreasing the radii ratio (R2/R1) of the ring and clearance ratio (c1/c2), in the other hand, the coefficient of friction increases with increasing the clearance and radii ratios, while decreases with incre4asing the bearing to journal speed ratio (γ). It is shown during this work that different operating conditions are greatly enhanced the performance
... Show MoreIn most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con
... Show MoreRate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal. The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in
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