Abstract

Geological and operational uncertainties usually impair the ability of operators to achieve technical and economic goals of a drilling project. Use of real-time data integrated to the earth model has recently reduced the above uncertainties, thus improving project performance. However, the above solution has only addressed part of the overall problem of optimizing the well's economics, it cannot easily cope with the rapidly increasing amounts of data collected while drilling, and it has not been fully integrated with the control of operations yet. Therefore, we propose a multilayer and multiscale integrated strategy for decision-making while drilling and in well intervention and maximi. The proposed strategy aims to simultaneously optimize in Real-time the following four objectives

  • operational drilling performance,

  • initial well completion design,

  • well productivity and

  • value creation.

By seeking to optimize an overall integrated objective rather than individual ones, the proposed strategy creates the possibility of achieving a solution that is superior to the aggregate of individually optimized solutions.

In this paper we outline the strategy mentioned above and discuss recent applications that support our proposition.

Introduction

Well construction and maintenance expenditures represent at least 50% of any field exploitation capital and operating expenses (Saputelli, 1999). In addition, planned expenditures and execution times often deviate from actual ones because of

  • poor characterization of reservoir rock and fluids, and

  • poor anticipation and management of abnormal operational situations

Because of such inherent uncertainties on reservoir geology and operations, real-time decision-making (while drilling and/or in workover) has traditionally played a crucial role in the construction and maintenance of any well. Improvising at the rig site has been the mainstay of the past; the results have not always been optimum.

Recently, many sensors have been installed at the rig site in both the surface and downhole to measure some of the important operational parameters such as bit rotation, mud weight, stress, weight on bit, and reservoir properties such as pressure, grain, porosity and permeability distribution. Real-time data provided by such sensors have been integrated to the earth model, resulting in reduction of uncertainty to some extent. Also, real-time data have been used to control individual rig operations such as rotary steerable directional drilling, hydraulic fracturing, blow-out prevention, and well completion. Similarly, technologies allow integrated reservoir study teams to access and assess vast amounts of information, including drilling performance, and be able to decide "at the last minute" about well architecture, completion and value creation.

However,

  • Each of the above solutions addresses an individual piece of the overall problem

  • Oftenly, current methods for data interpretation and decision-making cannot easily cope with the rapidly increasing amounts of real-time data collected while drilling. Such a poorly defined decision-making process usually consumes daily rig-time and, indeed, may not be quite accurate or encompassing

  • Real-time geological characterization and control of operations have not been integrated to produce a global solution, i.e. impact drilling operation in real-time

The above realizations indicate that there are many opportunities for improving the decision-making process. Therefore, we propose a multilayer and multiscale integrated strategy for decision-making while drilling and in well intervention. This strategy aims to simultaneously optimize in Real-time the following four objectives

  1. operational drilling performance,

  2. initial well completion design,

  3. well productivity, and

  4. value creation.

This content is only available via PDF.
You can access this article if you purchase or spend a download.