A Pre-drill Computer Model for Predicting Post-drill Well Gradients
Drilling wildcat or exploration wells without the knowledge of the well gradients (pore gradient, fracture gradient, and overburden gradient) poses a great risk to operators economically and operationally. This project proposes a simple but robust compute
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Abstract Drilling wildcat or exploration wells without the knowledge of the well gradients (pore gradient, fracture gradient, and overburden gradient) poses a great risk to operators economically and operationally. This project proposes a simple but robust computer model for predicting pre-drill well gradients. Two-way time (TWT) and average velocity (AV) from a field seismic data were adopted in the model development. Results obtained from the pre-drill well gradient model were validated against post-drill well gradient data from three wells in the same field. A very good statistical agreement between the pre-drill model and the post-drill field data was achieved. The pre-drill model predicted the post-drill gradient data with mean absolute percent error (MAPE) from 4.64 to 6.23%, thus indicating the robustness of the proposed model. Similarly, regression success index, R2, values between the pre-drill and post-drill well gradient data ranged from 0.830 to 0.985 for all datasets (DS1), (DS2), and (DS3). Information from this study is very essential in making better and sound decisions about mud weight design and casing program before drilling wildcat wells especially in deep offshore environment where there is a narrow window between the pore and fracture gradients. Keywords Well gradients Wildcat well
Seismic data Two-way time Average velocity
1 Introduction The accurate prediction of well gradients such as pore gradient, fracture gradient, and overburden gradient is of great importance in designing drilling program for wildcat or exploratory wells. The unavailability of offset or near-well data in a new field usually requires that the estimation of pre-drill well gradients be made using T.N. Ofei (&) D.J. Jorge Petroleum Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2017 M. Awang et al. (eds.), ICIPEG 2016, DOI 10.1007/978-981-10-3650-7_64
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seismic data which includes two-way time (TWT) and average velocity (AV). The estimation of these well gradients is a prerequisite for designing an effective mud weight and casing program, thus ensuring the drilling operations are carried out safely and economically. The knowledge of the subsurface pressure enables the drilling operator to prevent critical drilling problems such as formation fracture and loss of drilling mud, as well as avoiding potential influx of formation fluids into the wellbore which may eventually lead to a blowout if uncontrolled. A further use of pre-drill well gradients helps the drilling team to design cementing program, casing setting points, and casing design. Additionally, pre-drill well gradients are also useful for the optimization of hydraulic program, bit selection, blowout preventers (BOPs) and well head selection, drilling rig dimensioning, equipment selection, detection of potential hole problems, and forecast of operation costs. By applying an appropriate transformation model, two-way time and av
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