Lateef Akanji | University of Salford (original) (raw)

Papers by Lateef Akanji

An artificial intelligence technique based on five (5) layered feedforward backpropagation algori... more An artificial intelligence technique based on five (5) layered feedforward backpropagation algorithm is applied in this study for technical screening of enhanced oil recovery (EOR) methods. Explicit knowledge pattern associated with the field data are extracted by taking advantage of the robustness of fuzzy logic reasoning and learning capability of neural networks. Associated field data from successful EOR projects include parameters such as depth, porosity, permeability, viscosity, oil API and oil saturation. These parameters were used as input and predicted output in the training and validation processes, respectively. The developed model was then tested by using data set from Block T of the Angolan oilfield. Sensitivity analysis was performed between the Mandani and the Takagi Sugero (TSK) model approach incorporated in the algorithm. The results of the sensitivity analysis have shown the robustness of the ANFIS approach in comparison to other approaches for the prediction of suitable EOR technique. Five nonregression models (linear, potential, logarithm, power and polynomial) were applied to evaluate the accuracy of the model between the trained and the tested data set. The results of simulation show that hydrocarbon gas, polymer, combustion and CO 2 are the suitable EOR techniques and could be used for further experimental and numerical studies.

Energies, 2017

In this work, a neuro-fuzzy (NF) simulation study was conducted in order to screen candidate rese... more In this work, a neuro-fuzzy (NF) simulation study was conducted in order to screen candidate reservoirs for enhanced oil recovery (EOR) projects in Angolan oilfields. First, a knowledge pattern is extracted by combining both the searching potential of fuzzy-logic (FL) and the learning capability of neural network (NN) to make a priori decisions. The extracted knowledge pattern is validated against rock and fluid data trained from successful EOR projects around the world. Then, data from Block K offshore Angolan oilfields are then mined and analysed using box-plot technique for the investigation of the degree of suitability for EOR projects. The trained and validated model is then tested on the Angolan field data (Block K) where EOR application is yet to be fully established. The results from the NF simulation technique applied in this investigation show that polymer, hydrocarbon gas, and combustion are the suitable EOR techniques.

Physical Review E, 2009

We study through numerical simulations the dependence of the hydraulic permeability of granular m... more We study through numerical simulations the dependence of the hydraulic permeability of granular materials on the particle shape and the grain size distribution. Several models of sand are constructed by simulating the settling under gravity of the grains; the friction coefficient is varied to construct packs of different porosity. The size distribution and shapes of the grains mimic real sands. Fluid flow is simulated in the resulting packs using a finite element method and the permeability of the packs is successfully compared with available experimental data. Packs of nonspherical particles are less permeable than sphere packs of the same porosity. Our results indicate that the details of grain shape and size distribution have only a small effect on the permeabilty of the systems studied.

Transport in Porous Media, 2010

We present a finite element (FEM) simulation method for pore geometry fluid flow. Within the pore... more We present a finite element (FEM) simulation method for pore geometry fluid flow. Within the pore space, we solve the single-phase Reynold's lubrication equation-a simplified form of the incompressible Navier-Stokes equation yielding the velocity field in a two-step solution approach. (1) Laplace's equation is solved with homogeneous boundary conditions and a right-hand source term, (2) pore pressure is computed, and the velocity field obtained for no slip conditions at the grain boundaries. From the computed velocity field, we estimate the effective permeability of porous media samples characterized by section micrographs or micro-CT scans. This two-step process is much simpler than solving the full Navier-Stokes equation and, therefore, provides the opportunity to study pore geometries with hundreds of thousands of pores in a computationally more cost effective manner than solving the full Navier-Stokes' equation. Given the realistic laminar flow field, dispersion in the medium can also be estimated. Our numerical model is verified with an analytical solution and validated on two 2D micro-CT scans from samples, the permeabilities, and porosities of which were pre-determined in laboratory experiments. Comparisons were also made with published experimental, approximate, and exact permeability data. With the future aim to simulate multiphase flow within the pore space, we also compute the radii and derive capillary pressure from the Young-Laplace's equation. This permits the determination of model parameters for the classical Brooks-Corey and van-Genuchten models, so that relative permeabilities can be estimated.

Physical Review E, 2009

We study through numerical simulations the dependence of the hydraulic permeability of granular m... more We study through numerical simulations the dependence of the hydraulic permeability of granular materials on the particle shape and the grain size distribution. Several models of sand are constructed by simulating the settling under gravity of the grains; the friction coefficient is varied to construct packs of different porosity. The size distribution and shapes of the grains mimic real sands. Fluid flow is simulated in the resulting packs using a finite element method and the permeability of the packs is successfully compared with available experimental data. Packs of nonspherical particles are less permeable than sphere packs of the same porosity. Our results indicate that the details of grain shape and size distribution have only a small effect on the permeabilty of the systems studied.

An artificial intelligence technique based on five (5) layered feedforward backpropagation algori... more An artificial intelligence technique based on five (5) layered feedforward backpropagation algorithm is applied in this study for technical screening of enhanced oil recovery (EOR) methods. Explicit knowledge pattern associated with the field data are extracted by taking advantage of the robustness of fuzzy logic reasoning and learning capability of neural networks. Associated field data from successful EOR projects include parameters such as depth, porosity, permeability, viscosity, oil API and oil saturation. These parameters were used as input and predicted output in the training and validation processes, respectively. The developed model was then tested by using data set from Block T of the Angolan oilfield. Sensitivity analysis was performed between the Mandani and the Takagi Sugero (TSK) model approach incorporated in the algorithm. The results of the sensitivity analysis have shown the robustness of the ANFIS approach in comparison to other approaches for the prediction of suitable EOR technique. Five nonregression models (linear, potential, logarithm, power and polynomial) were applied to evaluate the accuracy of the model between the trained and the tested data set. The results of simulation show that hydrocarbon gas, polymer, combustion and CO 2 are the suitable EOR techniques and could be used for further experimental and numerical studies.

Energies, 2017

In this work, a neuro-fuzzy (NF) simulation study was conducted in order to screen candidate rese... more In this work, a neuro-fuzzy (NF) simulation study was conducted in order to screen candidate reservoirs for enhanced oil recovery (EOR) projects in Angolan oilfields. First, a knowledge pattern is extracted by combining both the searching potential of fuzzy-logic (FL) and the learning capability of neural network (NN) to make a priori decisions. The extracted knowledge pattern is validated against rock and fluid data trained from successful EOR projects around the world. Then, data from Block K offshore Angolan oilfields are then mined and analysed using box-plot technique for the investigation of the degree of suitability for EOR projects. The trained and validated model is then tested on the Angolan field data (Block K) where EOR application is yet to be fully established. The results from the NF simulation technique applied in this investigation show that polymer, hydrocarbon gas, and combustion are the suitable EOR techniques.

Physical Review E, 2009

We study through numerical simulations the dependence of the hydraulic permeability of granular m... more We study through numerical simulations the dependence of the hydraulic permeability of granular materials on the particle shape and the grain size distribution. Several models of sand are constructed by simulating the settling under gravity of the grains; the friction coefficient is varied to construct packs of different porosity. The size distribution and shapes of the grains mimic real sands. Fluid flow is simulated in the resulting packs using a finite element method and the permeability of the packs is successfully compared with available experimental data. Packs of nonspherical particles are less permeable than sphere packs of the same porosity. Our results indicate that the details of grain shape and size distribution have only a small effect on the permeabilty of the systems studied.

Transport in Porous Media, 2010

We present a finite element (FEM) simulation method for pore geometry fluid flow. Within the pore... more We present a finite element (FEM) simulation method for pore geometry fluid flow. Within the pore space, we solve the single-phase Reynold's lubrication equation-a simplified form of the incompressible Navier-Stokes equation yielding the velocity field in a two-step solution approach. (1) Laplace's equation is solved with homogeneous boundary conditions and a right-hand source term, (2) pore pressure is computed, and the velocity field obtained for no slip conditions at the grain boundaries. From the computed velocity field, we estimate the effective permeability of porous media samples characterized by section micrographs or micro-CT scans. This two-step process is much simpler than solving the full Navier-Stokes equation and, therefore, provides the opportunity to study pore geometries with hundreds of thousands of pores in a computationally more cost effective manner than solving the full Navier-Stokes' equation. Given the realistic laminar flow field, dispersion in the medium can also be estimated. Our numerical model is verified with an analytical solution and validated on two 2D micro-CT scans from samples, the permeabilities, and porosities of which were pre-determined in laboratory experiments. Comparisons were also made with published experimental, approximate, and exact permeability data. With the future aim to simulate multiphase flow within the pore space, we also compute the radii and derive capillary pressure from the Young-Laplace's equation. This permits the determination of model parameters for the classical Brooks-Corey and van-Genuchten models, so that relative permeabilities can be estimated.

Physical Review E, 2009

We study through numerical simulations the dependence of the hydraulic permeability of granular m... more We study through numerical simulations the dependence of the hydraulic permeability of granular materials on the particle shape and the grain size distribution. Several models of sand are constructed by simulating the settling under gravity of the grains; the friction coefficient is varied to construct packs of different porosity. The size distribution and shapes of the grains mimic real sands. Fluid flow is simulated in the resulting packs using a finite element method and the permeability of the packs is successfully compared with available experimental data. Packs of nonspherical particles are less permeable than sphere packs of the same porosity. Our results indicate that the details of grain shape and size distribution have only a small effect on the permeabilty of the systems studied.