The Mouydir basin is considered the less explored basin where only low-quality seismic 2D data is available. The negative wells were drilled on structures recognized through geological maps, gravity, and seismic refraction data. The Cambro-Ordovician is the main reservoir in the Mouydir basin. It is characterized by tight sandstone where the permeability ranges from 0.01 to 1 mD and porosity from 3% to 6% in the Cambrian and the Ordovician, respectively. A specific workflow is proposed to bring new insight and guide the future exploration in this basin using surface and subsurface data. The workflow includes surface data such as geological maps and digital elevation models and subsurface data such as gravity, seismic 2D, and core. The 3D fracture model is used to understand the fractures’ distribution, fractures’ connectivity, and fractures’ kinematics. The outcomes could be used to predict fractures’ extension and occurrence in the subsurface. The drilling of a horizontal pilot well perpendicular to the maximum horizontal stress could be a beginning of a new exploration era in Mouydir basin.
Skip Nav Destination
3rd International Discrete Fracture Network Engineering Conference
June 29–July 1, 2022
Santa Fe, New Mexico, USA
Fracture Detection and Prediction Using Subsurface Data and Reservoir Analog
Sofiane Djezzar;
Sofiane Djezzar
University of North Dakota, Grand Forks
Search for other works by this author on:
Aldjia Boualam;
Aldjia Boualam
University of North Dakota, Grand Forks
Search for other works by this author on:
Habib Ouadi;
Habib Ouadi
University of North Dakota, Grand Forks
Search for other works by this author on:
Aimen Laalam;
Aimen Laalam
University of North Dakota, Grand Forks
Search for other works by this author on:
Nadia Mouedden;
Nadia Mouedden
University of North Dakota, Grand Forks
Search for other works by this author on:
Ahmed Merzoug;
Ahmed Merzoug
University of North Dakota, Grand Forks
Search for other works by this author on:
Abderraouf Chemmakh
Abderraouf Chemmakh
University of North Dakota, Grand Forks
Search for other works by this author on:
Paper presented at the 3rd International Discrete Fracture Network Engineering Conference, Santa Fe, New Mexico, USA, June 2022.
Paper Number:
ARMA-DFNE-22-0037
Published:
June 29 2022
Citation
Djezzar, Sofiane, Boualam, Aldjia, Ouadi, Habib, Laalam, Aimen, Mouedden, Nadia, Merzoug, Ahmed, and Abderraouf Chemmakh. "Fracture Detection and Prediction Using Subsurface Data and Reservoir Analog." Paper presented at the 3rd International Discrete Fracture Network Engineering Conference, Santa Fe, New Mexico, USA, June 2022. doi: https://doi.org/10.56952/ARMA-DFNE-22-0037
Download citation file:
Sign in
Don't already have an account? Register
Personal Account
You could not be signed in. Please check your username and password and try again.
Could not validate captcha. Please try again.
Pay-Per-View Access
$20.00
Advertisement
23
Views
Advertisement
Suggested Reading
Advertisement