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Dr Mohammad Sayyafzadeh

Telephone +61 8 8313 8023
Position Lecturer
Email mohammad.sayyafzadeh@adelaide.edu.au
Building Santos Petroleum Engineering Building
Floor/Room 3 02a
Campus North Terrace
Org Unit Australian School of Petroleum

To link to this page, please use the following URL:
http://www.adelaide.edu.au/directory/mohammad.sayyafzadeh

Biography/ Background

Mohammad Sayyafzadeh is a Lecturer at Australian School of Petroleum. He holds a PhD degree in Petroleum Engineering from the University of Adelaide, a M.Sc. degree in Reservoir Engineering and a B.Sc. degree in Chemical Engineering from Tehran Polytechnic. He was formerly a research fellow at the University of Tehran in Reservoir Engineering group who successfully managed to receive two appreciable grants from oil companies.  

His teaching interests include mathematical and numerical modelling of fluid flow in reservoir rocks, inverse modelling and optimisation, geostatistics and production engineering.

Mohammad’s research interests are categorised into two major areas,

i. Mathematics and theoretical Computer Science with an emphasis on applications within the fields of reservoir engineering, such as probabilistic inverse modelling and uncertainty quantification, dimensionality reduction (reparameterisation) by wavelet transforms, computational costs reduction by surrogate-modelling, Markov chain Monte Carlo algorithms for sampling non-Gaussian multivariate posterior distributions and development of Evolutionary Computation algorithms for history matching and field development optimisation.  

ii. Reservoir Engineering with an emphasis on unconventional resources, such as modelling and simulation of enhanced coalbed methane (ECBM) recovery by injecting a foreign gas, simulation of CO2 sequestration in coal seams, simulation of flow-back after hydraulic fracing in tight sand reservoirs, well-placement optimisation in coal seam plays, and development of fast simulator for performance forecasting of gas (miscible and immiscible) and water flooding in oil reservoirs.

His Ph.D. study was sponsored by the University of Adelaide and SANTOS Ltd. During the study, Mohammad developed a software framework in MATLAB which allows us to perform history matching, infill drilling, production optimisation and uncertainty quantification semi-automatic. His thesis has been acknowledged by an award from the University (Dean's Commendation for Doctoral Thesis Excellence). Along with his Ph.D. study, he was involved in two other projects on unconventional resources (CSG) in which the target was gas recovery increment and water production reduction.

Mohammad has also contributed in publishing several papers and also serves as a reviewer of a few prestigious journals.

Qualifications

Ph.D.: The University of Adelaide, Petroleum Engineering, 2010-2013

M.Sc.: Amirkabir University of Technology (Tehran Polytechnic), Petroleum Engineering – Hydrocarbon Reservoir, 2007-2010

B.Sc.: Amirkabir University of Technology (Tehran Polytechnic), Chemical Engineering - Petrochemical, 2003-2007

Awards & Achievements

a.    Dean's Commendation for Doctoral Thesis Excellence

b.    Living Expenses Scholarship for international students from SANTOS Co. to undertake PhD

c.    Tuition Fee Scholarship for international students from the University of Adelaide to undertake PhD

d.    SPE SA chapter scholarship 2011 

e.    SPE SA chapter scholarship 2013 

Teaching Interests

1.   Reservoir Simulation, (third year level subject): The course gives the theoretical basis and practical fundamentals for mathematical modelling and numerical simulation of fluid flow in petroleum reservoirs. The governing laws and equations required for the modelling of single-phase and multi-phase flow in porous media, such as mass conservation, Darcy, equation of state, rock compressibility, capillary pressure and relative permeability, are reviewed. By combining these laws and equations, the corresponding partial differential equations are derived. The numerical methods for solving the governing partial differential equations using finite difference methods are presented.

 

2.   Reservoir Characterisation and Modelling, (third year level subject): The course has three main components. 1) Data sources, quality and analysis, including spatial analysis. 2) Generating 3D models of reservoir properties - classical gridding and mapping, kriging as a data-driven (variogram) form of classical mapping (estimation) and a means of data integration. Simulation techniques are introduced as a means of assessing uncertainty resulting from heterogeneity. 3) Scaling of grids and property models for the purpose of reservoir simulation is the final topic.

 

3.    Introduction to Petroleum Engineering, (first year level subject): The aim of the course is to provide students with a broad overview of introduction to petroleum engineering in order that advanced courses in subsequent years can be understood within a broader petroleum engineering context. 

Research Interests

a)    Probabilistic inverse modelling in highly nonlinear problems, such as history matching

b)    Enhanced Coal Bed Methane (ECBM) recovery by gas injection 

c)    Infill drilling and well placement optimisation in unconventional resources

d)    Application of surrogate-assisted algorithms in history matching and production optimisation

e)    Uncertainty quantification of reservoir model parameters

f)     Dimensionality reduction (feature extraction) of vector model space by linear and nonlinear mapping transformers  

g)    Application of Evolutionary Computation methods, such as genetic algorithm, artificial bee colony and artificial neural network, in Petroleum Engineering

h)    Markov chain Monte Carlo algorithms for sampling non-Gaussian multivariate posterior distributions

Research Funding

  • Full-parameterised history matching by stochastic wavelet bases for highly heterogeneous reservoirs (Lead Investigator), SANTOS Ltd, 79,000 AUD.
  • Enhanced gas recovery using improved flow-back in fracture treatment in tight gas reservoirs, Cooper Basin, (Co-Investigator), client: SANTOS Ltd, 80,000 AUD.

Publications

Journals:

i. O'Reilly DI, Haghighi M, Flett MA, Sayyafzadeh M. Pressure and rate transient analysis of artificially lifted drawdown tests using cyclic Pump Off Controllers. Journal of Petroleum Science and Engineering. 2016.

ii. Sayyafzadeh M, Keshavarz A, Rahman A, Alias M, Dong KA, Manser M. Investigation of varying-composition gas injection for coalbed methane recovery enhancement: A simulation-based study. Journal of Natural Gas Science and Engineering. 2015.

iii. Sayyafzadeh M, Mamghaderi A, Pourafshary P, Haghighi M. A fast simulator for hydrocarbon reservoirs during gas injection. Petroleum Science and Technology. 2014 2014/10/18:2434-42.

iv. Salmachi A, Bonyadi MR, Sayyafzadeh M, Haghighi M. Identification of potential locations for well placement in developed coalbed methane reservoirs. International Journal of Coal Geology. 2014 9/1/;131(0):250-62.

v. Sayyafzadeh M, Haghighi M. An Assessment of different model-management techniques in history matching problems for reservoir modelling. Australian Petroleum Production and Exploration Association Journal. 2013;53:391-406.

vi. Salmachi A, Sayyafzadeh M, Haghighi M. Infill well placement optimization in coal bed methane reservoirs using genetic algorithm. Fuel. 2013.

vii. Sayyafzadeh M, Haghighi M, Bolouri K, Arjomand E. Reservoir characterisation using artificial bee colony optimisation. Australian Petroleum Production and Exploration Association Journal. 2012.

viii. Sayyafzadeh M, Pourafshary P, Haghighi M, Rashidi F. Application of transfer functions to model water injection in hydrocarbon reservoir. Journal of Petroleum Science and Engineering. 2011;78(1):139-48.

ix. Sayyafzadeh, M. & Keshavarz, A. (2016). Optimisation of gas mixture injection for enhanced coalbed methane recovery using a parallel genetic algorithm. Journal of Natural Gas Science and Engineering, (accepted)

x. Sayyafzadeh, M. (2016). Reducing the computation time of well placement optimisation problems using self- adaptive metamodelling. Computational Geosciences Journal, (submitted)

xi. Sayyafzadeh, M. (2016). Uncertainty quantification using a self-supervised surrogate-assisted Metropolis-Hasting algorithm. ECMOR XV Special Issue, Computational Geosciences Journal (submitted)

xiv. Sarkar, S., Haghighi, M. & Sayyafzadeh, M. (2016). Modeling of fracturing fluid formation damage in tight gas reservoirs after multistage hydraulic fracture operation with pre-existing natural fractures – a case study from Cooper Basin, South Australia, Journal of Natural Gas Science and Engineering, (submitted)

 

Conferences:

i. Sayyafzadeh M., Uncertainty quantification using a self-supervised surrogate-assisted Metropolis-Hasting algorithm. 29/08/2016/. ECMOR XV: European Conference on Mathematics of Oil Recovery;2016 

ii. Sayyafzadeh M., A Self-Adaptive Surrogate-Assisted Evolutionary Algorithm for Well Placement Optimization Problems. 2015/10/20/. SPE: Society of Petroleum Engineers; 2015.

iii. Sayyafzadeh M., History Matching by Online Metamodeling. 2015/9/14/. SPE: Society of Petroleum Engineers; 2015.

iv. Sayyafzadeh M., Keshavarz A, Alias ARM, Dong KA, Manser M. Enhancing Coal Bed Methane Recovery by Varying-Composition Gas Injection. 2015/10/20/. SPE: Society of Petroleum Engineers; 2015.

v. Wang K, Peng X, Du Z, Haghighi M, Sayyafzadeh M., DFN Model for Flow Simulation in Hydraulically Fractured Wells With Pre-Existing Natural Fractures Using Unstructured Quadrilateral Grids. 2015/11/9/. SPE: Society of Petroleum Engineers; 2015.

vi. Sayyafzadeh M., Haghighi M. High-Resolution Reservoir Modeling Using Image Fusion Technique in History Matching Problems. 2013/6/10/. SPE: Society of Petroleum Engineers; 2013.

vii. Sayyafzadeh M., Haghighi M, Carter J. Regularization in History Matching Using Multi-Objective Genetic Algorithm and Bayesian Framework.  SPE EUROPEC 2012  Copenhagen, Denmark: Society of Petroleum Engineers; 2012.

viii. Sayyafzadeh M., Pourafshari P, Rashidi F. A Novel Method to Model Water-Flooding via Transfer Functions Approach.  SPE Project and Facilities Challenges Conference at METS; 01/01/2011; Doha, Qatar2011.

ix. Sayyafzadeh M., Mamghaderi A, Pourafshari P, Haghighi M. A New Method to Forecast Reservoir Performance during Immiscible and Miscible Gas-Flooding via Transfer Functions Approach.  SPE Asia Pacific Oil and Gas Conference and Exhibition; 01/01/2011; Jakarta, Indonesia2011.

x. Sayyafzadeh M., Pourafshari P, Rashidi F. Increasing Ultimate Oil Recovery by Infill Drilling and Converting Weak Production Wells to Injection Wells Using Streamline Simulation.  International Oil and Gas Conference and Exhibition in China; Beijing, China: SPE Society of Petroleum Engineers; 2010.

Professional Associations

·         Society of Petroleum Engineer (SPE) 

·         European Association of Geoscientists & Engineers (EAGE)

Community Engagement

Serve as a reviewer of

·         Fuel Journal

·         Mathematical Geosciences Journal

·         SPE Reservoir Evaluation and Engineering Journal

·         Journal of Petroleum Science and Engineering

·         Journal of Petroleum Exploration and Production Technology

·         Environmental Earth Sciences

·         EAGE/SPE 77th Annual Conference (EUROPEC)

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Entry last updated: Tuesday, 28 Mar 2017

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