Job getting story of an Oil & Gas pro.

Job Seekers,

I tell pros' stories and get them their desired job interviews. I share pros' stories in my posts. Today's story is of an Oil & Gas Pro.

About Me:

I worked on well-log interpretations on the Gulf of Mexico (GOM) offshore. Also, I worked on multiple offshore basins and plays, including GoM, Canada, Australia, and Trinidad & Tobago offshore wells. The experience gained from these exploration and operation projects made me a go-to guy on well-log interpretations.

Every Oil company wants to know how much oil can be produced from the reservoirs. This process requires an understanding of measurement physics and incorporating and interpreting these data using optimized methods. I do it with both inversions and machine learning algorithms.

• My estimation method to quantify gas saturation was more reliable than the traditional interpretation results from the resistivity log. It helps WPT (well planning team) to optimize the drilling process and save costs.?

I am excellent at developing inversions (linear and nonlinear, deterministic and stochastic) using obtained measurements and equations. The inversion results provide the optimized solution with minimized error. One of my recent works is Techlog QuantiElan equivalent multimineral inversion.

·??????It can provide forward modeling for both precomputations and input logs as well as inverted volumes of rock and fluid in the formation. Another example is the 1D and 2D NMR inversion that can estimate total porosity and permeability from raw magnetic decay sequences.

I am also capable of applying various machine-learning techniques to subsurface measurements. One case is my poster presented on BHP knowledge sharing day. Logs (GR, Resistivity, neutron porosity, and bulk density) from 37 Shenzi wells were applied into artificial neural networks to predict total porosity, total water saturation, clay volume, and air permeability.?

• The estimation results indicated that RMSE (root mean square error) for these four petrophysical parameters was greatly reduced compared to the traditional multi-linear regression (MLR) method.?

I am a problem solver. Therefore, I review the relationship between the provided measurements and output parameters for the given challenges and apply inversion algorithms or machine learning algorithms to find the best solutions by minimizing the cost function. My understanding of measurement physics and interpretation skills can bring significant value to the Occidental petrophysics team.?In addition, I learn how to make great teamwork by collaborating with geologists, geophysicists, completion engineers, and reservoir engineers. In addition, my colleagues and manager gave positive feedback for these works.

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