Abstract

Candidate selection is the key to the success of underbalanced drilling (UBD) projects. It is a question yet to be answered why sometimes UBD significantly improves productivity compared with conventional overbalanced drilling (OBD) practices but sometimes doesn't. To answer this question, we have performed an extensive reservoir engineering study to understand the mechanisms of productivity improvement from UBD. A single-well numerical model has been built that simulates the UBD process and the OBD process (while taking into account drilling filtration invasion, mud cake, and permanent formation damage) and their impact on production under a variety of reservoir conditions. Production rates are predicted for both UBD and OBD cases. Then, an incremental net present value (NPV) model has been used to analyze the economic benefits of UBD operations (if any) for all study cases. This paper describes our study methodology, models, simulation results, and analysis results and summarizes the reservoir criteria for successful UBD operations.

Reservoir properties play the most important role in the success of UBD operations. The study clearly demonstrates that UBD works for some reservoirs but not for all reservoirs. The study results provide a set of reservoir criteria that can be used as guidelines to choose potential UBD candidates.

Introduction

Underbalanced drilling (UBD) is a drilling operation in which the hydrostatic head of drilling fluid is less than formation pore pressure. Formation damage caused by conventional overbalanced drilling (OBD) can be reduced or eliminated with UBD, which may maintain original formation productivity. Formation damage mechanisms1,2 that may result from drilling operations and reduce productivity include

  • External drilling fluid/mud filtration invasion.

  • Fines migration.

  • Phase trapping.

  • Chemical incompatibility of invading fluid with the in-situ rock matrix and in-situ fluids.

  • Near-wellbore wettability alteration and surface adsorption effect.

Though majorities of the formation damages happen only in OBD operations, phase trapping can happen in both OBD and UBD operations. Phase trapping happens when water- or oil-based drilling mud filters into the formation in the near-wellbore region because of leakoff during overbalanced drilling operations or due to spontaneous imbibition in some situations during underbalanced drilling operations. Phase trapping can result in permanent entrapment of a portion or all of the invading fluid, causing adverse relative permeability effects and reducing oil or gas permeability in the near-wellbore regions.

There are four major drivers for UBD operations:

  • Lost circulation.

  • Differential sticking.

  • Rate of penetration and bit life problems.

  • Formation damage.

In the case of lost circulation, stuck pipe, and hard drilling, UBD is easily justified as a preferred operation, but it is difficult to quantify the reduction of formation damage and the productivity improvement from UBD.

An analytical model has been used in previous work3 to estimate the productivity index (PI) between UBD and OBD cases, with different skin factors, when a dynamic filtration process is not in the picture. The model is only suitable for a certain flow regime.

In this study, we have employed a numerical simulation method that considers formation damage mechanisms like drilling filtration invasion, mud cake, spontaneous imbibition, and permanent formation damage to investigate the productivity improvement mechanism by using UBD. Also, investigation is done to find suitable formation conditions in which UBD is a better choice to develop a reservoir.

Production rates are predicted for both UBD and OBD cases. Then, an incremental net present value (NPV) model is built to compare the economic benefits of UBD operations, from which one can easily determine if UBD wells perform better than OBD wells for given reservoir conditions.

The purpose of this study is to understand the UBD productivity improvement mechanisms; build a series of productivity index models (PI models) for different reservoir conditions; and build UBD candidate selection methods including an economic evaluation model.

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