Computational Modelling Techniques
Monte Carlo simulation is a process of running a model numerous times with a random selection from the input distributions for each variable. The results of these numerous scenarios can give you a "most likely" case, along with a statistical distribution to understand the risk or uncertainty involved. Computer programs make it easy to run thousands of random samplings quickly. one form of a volumetric model for oil in place, N, in terms of area, A; net pay, h; porosity, φ; water saturation, Sw; and formation volume factor, Bo.
\r\n N = 7,758Ahφ(1 - Sw) / Bo. Think of A, h, φ, Sw, and Bo as input parameters and N as the output.
\r\n The traditional tornado chart consists of bars of various length indicating the range of values of some key output (cost, reserves, NPV) associated with the full range of values.
\r\n Like tornado charts, a spider diagram is a traditional but limited. Again, one holds fixed all but one variable and examines how the output changes (usually measured as a percent change) as we vary that one input (usually by a few specific percentages). Typically, we might vary each input by 5, 10, and 20% and see how much the output changes. Often the percent change is not linear, causing the resulting graph to have broken line segments, accounting for the name: spider diagram
Related Conference of Computational Modelling Techniques
Computational Modelling Techniques Conference Speakers
- Advanced Drilling Technologies
- Advanced Natural Gas Engineering
- Advances in Petroleum Engineering
- Computational Modelling Techniques
- Computer Applications in Petroleum Engineering
- Environmental Impacts in Petroleum Engineering
- Field Development & Production Operations
- Fuels and Refining
- Geophysical Exploration
- Hydraulic Fracturing
- Major Challenges in Petroleum Industry
- Petroleum Distillation and Refining
- Petroleum Geology
- Petroleum Substitutes
- Petrophysics & Petrochemistry
- Processing units used in refineries
- Reservoir Engineering