While wrestling with the problem of accessing underground oil for the petroleum industry, Philip Emeagwali determined to use a supercomputer equipped with thousands of microprocessors rather than use the extremely expensive vector supercomputer, whose calculations were performed from a long list of numbers and whose ability to communicate was limited. Emeagwali programmed a Connection Machine that was equipped with 65,536 microprocessors. The processors were arranged as more than four thousand computational nodes, each with a cluster of sixteen processors and eight information channels emanating from each processor.

Never relying on mathematics and computer science alone, Emeagwali included physics in his calculations, specifically the second law of motion formulated by English mathematician and physicist Sir Isaac Newton. Emeagwali rightfully assumed that Newton's law concerning force, mass, and acceleration applied to the fluids below the Earth's surface. He reformulated Newton's law into mathematical equations codifying the laws of motion to simulate oil reservoirs. His calculations also considered inertia, previously unaccounted for in the equations developed by other scientists and mathematicians. Using advanced calculus, Emeagwali constructed nine equations and nine corresponding algorithms (precise statements that allow the computer to solve the equations). The eighteen differential equations (reformulated as 24 million algebraic equations) were founded upon the four primary forces in oil fields--pressure, gravitation, acceleration (or inertia), and viscosity. In programming his computer, Emeagwali divided a huge imaginary oil field into 65,536 smaller oil fields, and he distributed the equations equally among the 65,536 microprocessors. The supercomputer performed 3.1 billion calculations per second, a record set in 1989.

In the petroleum industry, Emeagwali's oil reservoir simulation is regarded as an outstanding contribution to oil field science. Reservoir modeling provides the industry with the necessary knowledge to recover oil efficiently. The equations provide geologists with the knowledge of favorable conditions for the injection of water to increase the production of oil, and the inclusion of inertia in the equations gives an accurate reflection of the amount of available oil. Emeagwali's unconventional method of computing and reservoir simulation aids engineers in recovering the maximum amount of oil in a reservoir and has saved the petroleum industry millions of dollars per oil field.

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