## 6 Examples
### Example 2--Characterization of a Fault Plane from PTA Data
In other words, this tool can generate 5 different types of synthetic well logs at any location within the seismic survey boundaries. In the development stage of this tool, seismic attributes extracted from 3D seismic data, 5 different types of well logs, and well coordinates are utilized. The developed synthetic well log tool is capable of generating well logs for vertical wells at specified locations. However, the very same tool can be used in generating logs for wells with complex architecture such as slanted wells and horizontal wells when the wellbore trajectory is defined. Figure 13 shows schematically how the first tool works. Figure 12: Curve fitting scheme applied to production histories. The second tool is developed to predict the oil flow rates and cumulative oil production profiles as a time series at any desired well location. It should be remembered that the final goal of the second tool is to predict the five production-profile related parameters as described in Figure 12. Once these five parameters are identified, it is a straightforward procedure to construct the predicted production profiles at the desired locations. Figure 14 highlights the significant parts of the workflow established for the second stage of the analysis and construction of potential hydrocarbon productivity distribution over the domain of interest. Figure 15 shows the predicted oil flow rates and cumulative production profiles for the average, best, and worst cases. In these comparisons, predicted production profiles are compared against the production data from the actual wells. The average absolute error reported in the average quality case is 16.66% (Figure 15a), in the best quality case is 9.86% (Figure 15b), and in the worst case is 18.59% (Figure 15c). These testing cases represent the results for wells that are not shown to the expert system during the training phase. It is observed that promisingly high-quality matches were obtained both for oil production rates and cumulative oil production. It should be noted that the cumulative production time series is not obtained by integrating area under the production rate profile but determined directly by the expert system. This approach ensures the invoking of an additional internal check on the predictions. The average absolute error for cumulative production as a function of time is found to be slightly larger than 5%. Figure 13: Schematic representation of the workflow for the first tool. After validating and successfully testing the tools that are developed in the first and second phases of development, the remaining objective is to establish a heat map displaying the expected productivity distributions over the entire field. By doing so, it will be possible to identify previously unnoticed sweet spots for infill drilling purposes. This is schematically illustrated in the last phase of the second stage tool development as shown in Figure 14. After sweeping the entire field, the heat maps generated are shown in Figure 16. The upper left panel is a heat map showing the expected flow rates in barrels per month three years after commencing the production. On this panel, in the central section, the elongated area with bright colors shows the location of the existing producing wells (compare with the panel at the bottom). Additionally, in the same panel, the sweet spots identified as a result of this study are marked with red ovals. Furthermore, in the upper right panel, the heat map displays the expected cumulative production at the end of three years. In both heat maps, some permeability channels identified are also highlighted with the help of the red colored arrows. Figure 14: Schematic representation of the workflow for the second tool. Figure 15: (**a**) Average quality case: average error in predicting curve fitting parameters is ~16.66%. (**b**) Best quality case: average error in predicting curve fitting parameters is ~9.86%. (**c**) Worst quality case: average error in predicting curve fitting parameters is ~18.59%.