Integration Of Seismic Variance Attribute With Stochastic Error Surfaces To Have A Better Definition Of Structural Uncertainty -a Case Study
Authors: Ghosh Dipankar , Al-Enezi Bashar , Al-Matar Dawood 
Published: March 2015

Abstract
Structural uncertainty is defined by creating stochastic error surfaces built on control points. Uncertainty is zero at the drilled locations and varies smoothly away from the wells. The other factor that enhances uncertainty is fault-zone. This study aimed at generating a composite model integrating these two determinants of structural uncertainty.
The study is done on Mauddud surface in part of the Greater Burgan Field, Kuwait. The seismic guided surface was created incorporating tops of 13 drilled wells. Sequential Gaussian Simulation was used to generate stochastic error surfaces having normal distribution using these 13 zero value control points as input.
Deviation of the actual Mauddud top from the given seismic surface was calculated to be to the tune of ±60&apos;. The stochastic error surfaces were multiplied with a constant so that the surfaces closely represent the perceived uncertainty captured in these drilled wells.
Seismic variance attribute was used to capture the uncertainty in fault zone. Variance was extracted on Mauddud surface from the variance cube generated. This variance surface was normalized with minimum and maximum values 1 and 6 respectively to use it as a multiplier to the stochastic error surfaces. The assumption was that the uncertainty will increase six times where there is maximum variance. The stochastic error surfaces were multiplied by the normalized variance surface to get the composite uncertainty.
This uncertainty model was used to predict the uncertainty of Mauddud top in some wells drilled subsequently. The actual tops were found to be within the P10-P90 range except for a graben well where it was beyond the range.
This study thus provided a model to quantify the range of uncertainty in predicting tops taking into account both distance from control points and uncertainty associated with fault zones as captured by seismic variance.

Introduction
Prediction of formation tops in wells prior to drilling is always associated with some amount of uncertainty. It happens due to uncertainty in our understanding and description of the reservoir. As the formation top depth is often related to expected oil column, assuming the depth of oil water interface is known, it is important to have a feel of the uncertainty at the time of selecting locations to be drilled. Also, knowledge of structural uncertainty helps the drilling engineer in designing the well and planning material requirement.
This study analyses two important sources of structural uncertainty. The first one is distance from the drilled wells. As you go farther from drilled locations the uncertainty increases smoothly away from the well. The other one is inherent structural variance of the surface concerned. The uncertainty is more in places where the surface is dipping at a steeper inclination or in places affected by faulting. This aspect of structural uncertainty is captured by seismic variance attribute. The study integrates these two components to generate a composite uncertainty multiplier that would give a quantitative measure of uncertainty over the entire study area.