Aymen Alhemdi | West Virginia University (original) (raw)
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Papers by Aymen Alhemdi
Day 2 Tue, October 04, 2022
One of the biggest challenges in drilling/completion/hydraulic fracturing optimization is determi... more One of the biggest challenges in drilling/completion/hydraulic fracturing optimization is determining the optimal parameters in the infinite space of possible solutions. Applying a comprehensive parametric study with various geomechanical properties using both a frac simulator and a reservoir simulator is low efficient. This study proposes a workflow for optimizing unconventional reservoir development using machine learning and artificial intelligence (AI) in conjunction with advanced geomechanical modeling. The workflow consists of four steps: in Step1, appropriate acoustic interpretation models are used for geomechanical and in-situ stress characterization. In Step2, unsupervised machine learning optimizes completion designs based on formation anisotropy and heterogeneity along a well. In step3, a training database is built by generating multiple cases based on various simulations guided by a smart sampling algorithm. Proxy models are trained and validated by feeding the training ...
Day 3 Thu, April 28, 2022
For optimizing the hydraulic fracture design in shales, it is challenging to understand the impac... more For optimizing the hydraulic fracture design in shales, it is challenging to understand the impact of several different parameters on fracture propagation and production, such as geomechanical properties and fracturing treatment parameters. Current frac simulators do not exhibit consideration of the anisotropy of rock elasticity in the shales. Additionally, using the fracture simulation linked with reservoir simulation for the parametric study is low efficient. Due to its lamination nature, shale has different geomechanical properties along with the directions vertically and horizontally. Anisotropic elastic properties and stresses lead to more complications for predicting the fracture. This study introduces a comprehensive workflow for fracturing design optimization by applying supervised machine learning. The research also aims to develop an algorithm that can help any shale reservoir optimize the pumping treatment design of hydraulic fracture. The workflow is divided into six ste...
Journal of Natural Gas Science and Engineering
Day 2 Wed, November 03, 2021
Slickwater-sand fracturing design is widely employed in Marcellus shale. The slickwater- sand cre... more Slickwater-sand fracturing design is widely employed in Marcellus shale. The slickwater- sand creates long skinny fractures and maximizes the stimulated reservoir volume (SRV). However, due to the fast settling of sand in the water, lots of upper and deeper areas are not sufficiently propped. Reducing sand size can lead to insufficient fracture conductivity. This study proposes to use three candidate ultra-lightweight proppants ULWPs to enhance the fractured well performance in unconventional reservoirs. In step 1, the current sand pumping design is input into an in-house P3D fracture propagation simulator to estimate the fracture geometry and proppant concentrations. Next, the distribution of proppant concentration converts to conductivity and then to fracture permeability. In the third step, the fracture permeability from the second step is input into a reservoir simulator to predict the cumulative production for history matching and calibration. In step 4, the three ULWPs are use...
The increasing demand of energy and the limited reserves of conventional reservoirs leads the ind... more The increasing demand of energy and the limited reserves of conventional reservoirs leads the industry to enhance and develop low permeability reservoirs in recent years which become increasingly important than ever before. Shale gas one of these reservoirs which has very low permeability and the production from this formation has been and continues to be challenging. Horizontal wells with multiple hydraulic fractures are the proven technology to produce economically from gas shale formations. One of the issues in shale gas reservoirs is to have an accurate and reliable estimation of ultimate recovery. The purpose of this research was to use the initial production history of Marcellus shale in order to predict the ultimate gas recovery of multiple fractured horizontal wells. A commercial reservoir simulator was utilized to create reservoir model with horizontal well fractured in multi stages. The impacts of a number of reservoir and fractures parameters were investigated. Matrix porosity, number of hydraulic fracture stages, and fracture half-length were found to impact on the gas recovery. DEDICATION My deepest gratefulness goes to my parents Abdullah and Dehiba for their unflagging love and unconditional support throughout my life and my studies I cannot thank you enough, May Allah protect them. I can't go on any further without thanking the rest of my family, brothers and sisters for their encouragement. I would like to dedicate my master to my dear wife Asma who stopped her study for me and my sweet son Sohib. Thank you for your help, support and endless motivation through entire my study.
Day 2 Tue, October 04, 2022
One of the biggest challenges in drilling/completion/hydraulic fracturing optimization is determi... more One of the biggest challenges in drilling/completion/hydraulic fracturing optimization is determining the optimal parameters in the infinite space of possible solutions. Applying a comprehensive parametric study with various geomechanical properties using both a frac simulator and a reservoir simulator is low efficient. This study proposes a workflow for optimizing unconventional reservoir development using machine learning and artificial intelligence (AI) in conjunction with advanced geomechanical modeling. The workflow consists of four steps: in Step1, appropriate acoustic interpretation models are used for geomechanical and in-situ stress characterization. In Step2, unsupervised machine learning optimizes completion designs based on formation anisotropy and heterogeneity along a well. In step3, a training database is built by generating multiple cases based on various simulations guided by a smart sampling algorithm. Proxy models are trained and validated by feeding the training ...
Day 3 Thu, April 28, 2022
For optimizing the hydraulic fracture design in shales, it is challenging to understand the impac... more For optimizing the hydraulic fracture design in shales, it is challenging to understand the impact of several different parameters on fracture propagation and production, such as geomechanical properties and fracturing treatment parameters. Current frac simulators do not exhibit consideration of the anisotropy of rock elasticity in the shales. Additionally, using the fracture simulation linked with reservoir simulation for the parametric study is low efficient. Due to its lamination nature, shale has different geomechanical properties along with the directions vertically and horizontally. Anisotropic elastic properties and stresses lead to more complications for predicting the fracture. This study introduces a comprehensive workflow for fracturing design optimization by applying supervised machine learning. The research also aims to develop an algorithm that can help any shale reservoir optimize the pumping treatment design of hydraulic fracture. The workflow is divided into six ste...
Journal of Natural Gas Science and Engineering
Day 2 Wed, November 03, 2021
Slickwater-sand fracturing design is widely employed in Marcellus shale. The slickwater- sand cre... more Slickwater-sand fracturing design is widely employed in Marcellus shale. The slickwater- sand creates long skinny fractures and maximizes the stimulated reservoir volume (SRV). However, due to the fast settling of sand in the water, lots of upper and deeper areas are not sufficiently propped. Reducing sand size can lead to insufficient fracture conductivity. This study proposes to use three candidate ultra-lightweight proppants ULWPs to enhance the fractured well performance in unconventional reservoirs. In step 1, the current sand pumping design is input into an in-house P3D fracture propagation simulator to estimate the fracture geometry and proppant concentrations. Next, the distribution of proppant concentration converts to conductivity and then to fracture permeability. In the third step, the fracture permeability from the second step is input into a reservoir simulator to predict the cumulative production for history matching and calibration. In step 4, the three ULWPs are use...
The increasing demand of energy and the limited reserves of conventional reservoirs leads the ind... more The increasing demand of energy and the limited reserves of conventional reservoirs leads the industry to enhance and develop low permeability reservoirs in recent years which become increasingly important than ever before. Shale gas one of these reservoirs which has very low permeability and the production from this formation has been and continues to be challenging. Horizontal wells with multiple hydraulic fractures are the proven technology to produce economically from gas shale formations. One of the issues in shale gas reservoirs is to have an accurate and reliable estimation of ultimate recovery. The purpose of this research was to use the initial production history of Marcellus shale in order to predict the ultimate gas recovery of multiple fractured horizontal wells. A commercial reservoir simulator was utilized to create reservoir model with horizontal well fractured in multi stages. The impacts of a number of reservoir and fractures parameters were investigated. Matrix porosity, number of hydraulic fracture stages, and fracture half-length were found to impact on the gas recovery. DEDICATION My deepest gratefulness goes to my parents Abdullah and Dehiba for their unflagging love and unconditional support throughout my life and my studies I cannot thank you enough, May Allah protect them. I can't go on any further without thanking the rest of my family, brothers and sisters for their encouragement. I would like to dedicate my master to my dear wife Asma who stopped her study for me and my sweet son Sohib. Thank you for your help, support and endless motivation through entire my study.