Quantitative Evaluation of Pre-Drilling Safety by Combining Analytic Hierarchy Process with Alternating Condition Expectation

Abstract

In order to avoid potential personnel and financial losses, the evaluation of pre-drilling safety is of great importance in oil and gas exploration and development. This paper presents a method of evaluating pre-drilling safety through combining the Analytic Hierarchy Process (AHP) with the Alternating Condition Expectation (ACE) method. An indicator system with a 9-3-1 structure was established, incorporating various unrestricted variables to describe the technical factor. Additionally, nine membership functions and weights were determined in order to build the AHP model by connecting the independent variables in the basic layer to dependent variables in the middle layer. Four transformed functions were also formulated to construct the ACE model by linking the middle variables to the pre-drilling safety value in the final layer. A total of 28 sets of on-site drilling data from three oilfields were collected for the establishment and verification of the AHP-ACE model. Average absolute error (AAE) and average absolute relative error (AARE) of the model to predict the training data are 0.03 and 4.29%, respectively, whereas the AAE and AARE for verification samples are 0.03 and 4.51%, respectively. The sensitivity ranking of the three potential variables is as follows: human factor exhibits the highest degree of sensitivity, followed by natural factor and technical factor, in descending order. The AHP-ACE model for pre-drilling safety assessment faces limitations in universal applicability and scope, particularly in real-time drilling activities. However, its potential for improvement lies in integrating insights from past operations and expanding the dataset to enhance accuracy and broaden safety assessment coverage. This method is not limited by blocks, which is of great significance to ensure drilling safety.