Call Us 080-41656200 (Mon-Sat: 10AM-8PM)
Free Shipping above Rs. 1499
Cash On Delivery*

Using Artificial Neural Networks in Reservoir Characterization


Marketed By :  Scholars' Press   Sold By :  Kamal Books International  
Delivery in :  10-12 Business Days


Check Your Delivery Options

Rs. 5,059

Availability: In stock

  • Product Description

The framework of this study is to convert observed measurements of reservoir data into characteristic information of the reservoir. Artificial neural network (ANN) technology is utilized in mapping/interpolating the non-linear complex relationship between observed measurements and reservoir characteristics. The proposed ANN methodology is applied towards analysing the pressure transient measurements collected from isotropic and anisotropic faulted dual-porosity gas reservoirs, as an inverse solution to formation characteristics, such as the permeability and porosity of the fracture and matrix systems, distance to the fault, orientation of the fault with respect to the principal flow directions, and sealing capacity of the fault are predicted using the reservoir fluid, rock, and bottom-hole pressure as the principal inputs. The main focus of this study is to develop a suitable network to obtain accurate prediction about desired reservoir characteristics of dual-porosity tight gas systems with a fault, and demonstrate the efficient processing power of ANN on this class of reservoir problems.

Product Specifications
SKU :COC92816
AuthorZhazar Toktabolat
Number of Pages144
Publishing Year2013-04-23T00:00:00.000
Edition1 st
Book TypeAerospace & aviation technology
Country of ManufactureIndia
Product BrandScholars' Press
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-10-08 00:00:00