American Univesity of Beirut

 Oil and Gas Exploration and Development Group

​​​​​​​Contributing towards a clean, sustainable and optimal exploitation of natural resources…

Oil and gas business is new to Lebanon. Given the uniqueness of this “one-off" opportunity, its impact on the country's economy and the embedded multi-layer complexity, it is an imposing duty that government, industry and academia consolidate efforts towards optimal and environmentally friendly exploitation of this national fortune. The Oil and Gas Exploration and Development Group (OGED), led by Assistant Professor Kassem Ghorayeb, focuses on field development planning under uncertainty with a focus on offshore Lebanon. Our goal is to evaluate the ranges of oil and gas initially in place and forecasting production at the accumulation, block and overall level accounting for uncertainty. This includes scenarios on potential phased development aiming at incrementally benefiting from the acquired data to maximize value of the offshore gas and oil development. 

Below is a list of Projects undertaken currently by OGED:

Comprehensive Literature Review and Assessment of the Regional
Experience in Offshore Gas Exploration and Development

One important step for research project consists of benefiting form available published information related to gas field exploration and development in “Israel", Egypt and Cyprus.

Despite the confidentially related to the oil and gas sector in the region, there is still a large literature that will provide invaluable information that would potentially help narrowing down the uncertainty impacting the Lebanese offshore gas development using these analogues and 2) avoiding “déjà vu" pitfalls.

For the purpose, a comprehensive literature review of publically available material from conferences, journals and web-published reports will take place. This includes

  • Geology of the Discovered Fields / Reservoirs
  • Drilling: Exploration and development wells
  • Development concepts and plans.
  • Infrastructure

As a result of the review, filtering and consolidation of the available information, comprehensive reports will be written summarizing the outcome. These reports will include a part on the recommendations on how the available published regional data could be systematically used to further understand our subsurface and guide the process of exploration and development scenarios offshore Lebanon.

Conceptual Field Development Planning Offshore Lebanon

This research used the offshore Lebanon data provided by the Lebanese Petroleum Administration (under a specific Confidentiality Agreement) and covers the following:

  • Literature Review – Uncertainty Analysis in Oil and Gas Exploration & Development
  • Data Review and Data Uncertainty Identification
  • HIIP and Recoverable Hydrocarbon Assessment under Uncertainty
  • Blocks and Accumulations Ranking, Exploration and Conceptual Development Plans under Uncertainty
  • Aggregated HIIP Estimates and Production Forecasting
  • Advancing the Uncertainty Management Methodologies

Well Placement Optimization in Field Development Planning

Field development optimization involves a large number of optimization variables resulting from the multidimensional space of well parameters. Manual assessment of the permutation of these variables yield an excessively large number of development scenarios and, hence, it is practically unfeasible in the process of field development planning. We have developed a “static optimizer / operator"; the so – called Black Hole Operator that work back to back with evolutionary algorithms and drastically reduce its computational cost by making the whole optimization process independent of the number and trajectory of wells involved. Work is continuing to improve the core evolutionary algorithm (PSO), optimization under uncertainty (multiple subsurface realizations), considering a comprehensive range of pressure maintenance plans, switching between different model resolutions and scheduling

Platform Placement Optimization in Field Development Planning

Platform placement optimization is an important task in the Field development planning process. The specific platform placement optimization problem aims at placing multiple platforms and assigning planned wells to these platforms while minimizing the typical objective function:  cumulative wells' distances from the platforms. Optimally placed platforms, therefore, minimizes CAPEX and improves hydrocarbon recovery.

The proposed methods in the literature exhibit limitations in terms of the number of platform placement optimization parameters and the comprehensiveness of the addressed problem. Recently, genetic algorithms were applied with promising results with regard to this challenge. In this paper, the genetic algorithm (GA) is compared to another stochastic, population-based method; the particle swarm optimization (PSO). Results show that, as the complexity of the problem is increased, PSO significantly outperforms GA in terms of both 1) convergence time and 2) objective function value.

Chemical Injection based Enhanced Oil Recovery in Hydrocarbon Reservoirs

A project started to understand the fundamentals of “Chemical Injection based Enhanced Oil Recovery in Hydrocarbon Reservoirs". QCM-D for the purpose. This research will help understanding the fundamentals of the interaction of oil/water/surface in the presence of surfactants and the impact of these surfactants on changing the wettability of the surface and, hence, improve water displacing oil from the surface. Very few people used QCM-D for such applications. Therefore, we believe that this research will lead to new and innovative results. The research will benefit from the cross-domain expertise in the Chemical and Petroleum Engineering Department.

Figure 1: Illustration of well placement optimization of horizontal well azimuth using the Blank Hole well placement algorithm.

Figure 2 : Schematic of BHPSO workflow

Figure 3: BHPSO vs. Stand-Alone EA Methods. Consistently Superior Performance

Figure 4: Platform Placement Optimization. Limitless Problem Complexity

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