During drilling operations, it is essential to keep the wellbore pressure within the maximum value of the fracture pressure and minimum value of the pore pressure of the formation. To handle this challenge, the fracture pressure of the formation must be known as it is significant to determining the mud window design. This study developed a correlation that could predict the formation fracture pressure in the Niger Delta deep offshore field. Two different fields were considered for this model named Field 1 and 2. From these fields, fracture pressure data were gotten from 21 wells during leak off test (LOT) at different casing shoe depths. While carrying-out the analysis of data, assumptions were made that the formations throughout the Niger Delta basin obeys the principle of horizontality. Also, that the fracture pressure at same depth is uniform with the pressure at other location in the Delta. Scatter plot was used as the tool for the data analysis. A line of best fit was drawn to arrive at the correlation. This correlation has an R2 coefficient values of 0.9969. In conclusion, the correlation gotten from this study for predicting fracture pressure has shown to align with some data sets from the Niger Delta fields with very little variation. This can be used for planning of further drilling operations in the Niger Delta to make it easier, faster and more economical.

The challenge of data availability for accurately assessing a location's level of corrosivity has lingered for so long and as such, researchers are constantly seeking factors with great influence that can assist in describing how corrosive a location will be toward buried oil and gas infrastructure. Alternative measures are required for making rapid and realistic investment decisions because accumulating these factors to make perfect sense is sometimes time-consuming and expensive. Using MATLAB mathematical computational analysis, this study capitalizes on this gap to build a 3D corrosivity signature and model for Delta state, Nigeria to aid in rapid and realistic investment decision-making. The soil pH and resistivity were identified as key variables that determine the extent of corrosion in this investigation. Vertical Electrical Soundings were utilized to collect soil resistivity data, which was then combined with the soil pH to create a 3D corrosivity signature and model with a 98% R-square factor. During the study, potential limitations were found, and recommendations were made.

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During drilling operations, it is essential to keep the wellbore pressure within the maximum value of the fracture pressure and minimum value of the pore pressure of the formation. To handle this challenge, the fracture pressure of the formation must be known as it is significant to determining the mud window design. This study developed a correlation that could predict the formation fracture pressure in the Niger Delta deep offshore field. Two different fields were considered for this model named Field 1 and 2. From these fields, fracture pressure data were gotten from 21 wells during leak off test (LOT) at different casing shoe depths. While carrying-out the analysis of data, assumptions were made that the formations throughout the Niger Delta basin obeys the principle of horizontality. Also, that the fracture pressure at same depth is uniform with the pressure at other location in the Delta. Scatter plot was used as the tool for the data analysis. A line of best fit was drawn to arrive at the correlation. This correlation has an R2 coefficient values of 0.9969. In conclusion, the correlation gotten from this study for predicting fracture pressure has shown to align with some data sets from the Niger Delta fields with very little variation. This can be used for planning of further drilling operations in the Niger Delta to make it easier, faster and more economical.

No abstract