Showing 4 results for Khoozan
Volume 1, Issue 2 (Fall & Winter 2014)
Abstract
Although the literal translations of the Qur'an seemed insufficient and unclear, and do not have enough adaption with Persian language, however in many cases these translations have strong points which make them better than modern translations. Some of the strong points of these translations are: accuracy in finding exact equivalents, consistency and cohesion with the text of the Qur'an, paying attention to the morphological and syntactic structures in the source language. On the other hand, Lack of eloquence, ignoring the deletions, literal translation of metaphors are some of the shortcomings of literal translations of Qur'an. In this regard, this paper is to study the advantages and disadvantages of following literal translations of Holy Quran: Dehlavi, Sharany, Mesbah-zadeh and Moezzi.
Volume 6, Issue 4 (Winter 2022)
Abstract
موضوع تحقیق: یکی از روشهای نوین در فرآیندهای افزایش بازیافت نفت از مخازن هیدروکربوری، بکارگیری امواج اولتراسونیک میباشد. در این تحقیق با استفاده از امواج اولتراسونیک و اعمال آن در یک مخزن نمونه مقیاس بزرگ، به بررسی اثر آن در ازدیاد برداشت نفت به روش عددی پرداخته شده است.
روش تحقیق: در این تحقیق فرایند مدلسازی با استفاده از نرم افزار متلب انجام شده است. ابتدا با تعیین محیط متخلخل میزان افزایش فشار حاصل از موج اولتراسونیک با توجه به حل معادلات صوت ( هلمهولتز) توسط جعبه ابزار k-waves متلب بررسی شده و سپس با تعیین مخزن نمونه و حل معادلات حاکم بر مخزن میزان تغییرات فشار حاصل از جریان سیال در حضور چاه تولیدی به بررسی اثر موج اولتراسونیک در ازدیاد برداشت نفت پرداخته میشود. در نهایت با توجه به تولید تجمعی در یک زمان مشخص از چاه تولیدی و تعیین بازیافت نفت از مخزن در حضور موج، به بررسی اثر پارامترهای موقعیت مکانی چاه و فاصله آن از منبع تولید موج، زمان شروع تولید موج، شیوهای اعمال موج (پالسی و پیوسته)، در یک فرکانس و توان بهینه پرداخته میشود.
نتایج اصلی: با توجه به نتایج بدست آمده از مدلسازی، هرچقدر زمان شروع اعمال موج به روزهای اول تولید نزدیکتر باشد، میزان بازیافت نفت نیز بیشتر میشود؛ به گونه ای که با شروع اعمال موج اولتراسونیک تحت توان 5 کیلووات و فرکانس 20 کیلوهرتز همزمان با تولید نفت چاه از روز اول، بازیافت نفت نسبت به بازیافت نفت در حالتی که شروع اعمال موج از روزهای پنجاه و نود باشد، به ترتیب %5/4 و %8 بیشتر شده است. بازیافت نفت درصورتی که موج در یک زمان مشخص بصورت پیوسته به مخزن اعمال شود به میزان 8/1% نسبت به حالتی که در همان زمان بصورت پالسی اعمال شود، بیشتر است .نتایج مدلسازی نشان میدهد که هرچقدر فاصله منبع تولید موج با چاه تولیدی کمتر باشد، افت فشار محدوده چاه کمتر شده و بازیافت نفت افزایش میابد. بطوری که طبق نتایج اگر منبع تولید موج در فاصله 200 فوتی از چاه تولیدی قرار گرفته باشد، نسبت به فاصله 1800 فوتی از چاه بازیافت نفت % 1/7 افزایش میابد.
Volume 8, Issue 1 (3-2024)
Abstract
Research topic:
The disparity between supply and demand is one of the main obstacles in transitioning from fossil fuels to renewable energy. Underground hydrogen storage derived from renewable sources is a suitable method for storing energy from these sources. However, a portion of the stored gas remains in the reservoir as cushion gas, which can add to the operational costs. It is therefore recommended to replace this cushion gas with less expensive alternatives, such as CO2 or sour gas, to reduce these costs. Nevertheless, this replacement can affect the purity and recovery factor of hydrogen, which can be controlled by specific operating parameters. This study will investigate how these parameters can be adjusted to maintain high purity and recovery factor for stored hydrogen.
Research Method:
In this section, a model of a partially depleted gas reservoir was initially constructed using the commercial simulator CMG. Following validation, this model was employed to evaluate the desired parameters. For this purpose, approximately 50% of the reservoir was depleted initially, followed by the injection of the cushion gas for one year. Subsequently, the hydrogen storage process was conducted over a period of 10 years. This research investigates the impact of various parameters, including the duration and rate of hydrogen injection and production, the soaking time and duration of cushion gas injection, the utilization of sour gas as the cushion gas, and the concentration of H2S within it, on the purity and recovery factor of the produced hydrogen.
Main results:
The results showed that increasing the rate of hydrogen injection and production enhances its purity and recovery factor. Reducing the injection period while increasing the extraction period decreases purity but improves recovery, provided that the extraction period does not exceed the injection period. Extending the cushion gas injection time and the interval between injection and hydrogen storage supports the purity and recovery factor of hydrogen. Additionally, in the cushion gas composition, increasing the proportion of H2S above 70% in the sour gas mixture reduces hydrogen purity and recovery by approximately 2% and 3%, respectively, confirming the potential of H2S as a cushion gas.
Volume 8, Issue 1 (3-2024)
Abstract
Research Subject:Drilling operations frequently encounter numerous challenges that can lead to significant financial, human, and environmental losses. Therefore, predicting potential problems before they occur and implementing necessary preventive measures is crucial to minimizing risks. In this context, this study investigates the impact of employing artificial intelligence (AI) algorithms to forecast drilling complications using real-time mud logging data collected from existing wells in an Iranian oilfield.
Research approach: A hybrid architecture combining Long Short-Term Memory (LSTM) and Fully Connected neural networks was developed for the identification and detection of anomalies such as kicks and stuck pipe. Given the scarcity of these anomalies in the dataset, which could adversely affect model accuracy and performance, the Synthetic Minority Oversampling Technique (SMOTE) was applied to balance class distribution and enhance the overall effectiveness of the network. Furthermore, the influence of varying hyperparameters on reducing network error was systematically analyzed.
Main Results: Various network architectures and structures were examined. The experimental results indicated that the optimal model achieved an accuracy of 94.45% on the testing dataset with the following hyperparameters: a lookback of 7, a learning rate of 0.001, a dropout rate of 0.2, a batch size of 32, and a four-layer network architecture with 512, 256, and 256 units in the first, second, and third hidden layers, respectively. This configuration yielded higher accuracy and fewer false alarms in anomaly detection compared to other tested models. Based on the obtained results, this approach demonstrates significant potential for real-time anomaly detection in drilling operations.
