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This paper outlines an extract of a software model for digitalization of the processes supporting upstream activities for onshore and offshore fields. Digitalization in this context means full automation of planning and a step change in the daily well integrity work. The planning process will produce digital programs and proceduresunderstandable to humans and computers. The software comprises building blocks for every engineering calculation. These are interlinked andconstructed such that their planning capacity can be improved by the users. Today, humans drive every step in engineering and planning. Digital well planning and operations will shift the role of humans towards feeding the planning process with experiences in digital format. Changing from text based learning to digital experience will improve planning and operations. Digitalization can also provide digital standards, governing documentation and automate administrative routines such as invoicing. Visualization of wells, their components, barrier envelopes and elements from plan to "as installed" will form a 3D interactive interface where users of different roles can retrieve information and see relevant engineering, modelling and integrity status. The software is planned to be cloud based and exploit local graphics hardware for optimal performance and response. This article gives an introduction to the planned functionality of a new Digital Life Cycle Well Integrity Model (LCWIM) which is under development. In addition to an overview of the functionality, digitalization is exemplified by automation of one of the LCWIM modules, namely casing wear prediction. The LCWIM will produce digital programs and procedures, which is a foundation for the next step in digitalization: automation of the drilling process. The focus of this paper is to depict a digital work process concerning well planning giving input to the operational phase and well integrity.

Casing wear poses a significant safety hazard during drilling and production of hydrocarbons. Failure to maintain integrity due to inaccurate casing wear estimation can cause severe accidents or preclude prospective operations. Current industry practice is to estimate casing wear during the planning phase of the well and subsequently use assumed operational parameters with inherent uncertainties. This paper aims to study how to utilize real-time data to improve the industry standard methodology and evaluate the benefit of the modification. The research was conducted by applying the model on data from a well on the Norwegian continental shelf. There were two main objectives of the research. Firstly, the industry standard approach to casing wear estimation was expanded to include real-time data. Application of real-time data to the industry standard method for estimating casing wear caused a significant difference in results. The approach using real-time data resulted in an estimate of more casing wear compared to the standard approach. Secondly, an algorithm for continuous prediction of casing wear at the end of operation was developed. The predictive algorithm resulted in consistently more accurate estimates in relation to the final value throughout the operation. With variations in input parameters and consecutive casing wear of this magnitude, well integrity cannot be ensured during operation without application of real-time data. The failure to maintain well integrity demonstrates the necessity of the proposed approach.

Summary As wells in modern operations are getting longer and more complex, assessing the effect of casing wear becomes ever more crucial. Degradation of the tubulars through mechanical wear reduces the pressure capacity significantly. In this paper, we use the finite element method (FEM) to analyze the stress distribution in degraded geometries and to assess reduction in collapse strength. A model for the collapse strength of the casing with a crescent-shaped wear groove is developed and its performance evaluated in relation to experimental data. The model was created by using the Buckingham Pi theorem to make generalized empirical expressions for yield and elastic collapse of tubulars. Finite element analysis (FEA) of 135 geometries was used in the development of the model. The results show that the generalized expressions capture the trends observed in the FEA accurately and match the experimental data from six tubular collapse tests with an average relative difference in collapse pressure of 5.2%.

Emerging technologies are expected to provide step changes in many areas within planning, making and production of wells. The main topic of this paper covers in a digital workflow, where the different disciplines contributions to well integrity are expected to be on a fully digital format. All phases in the lifecycle of wells are integrated into one digital process, where possible improvements are enabled by the transition from a human oriented work process to a software oriented (human supported) process. This transition has taken place in several other comparable energy and capital-intensive industries. Today, some wells have the new fiber optics that enables a range of opportunities for improvement of well integrity. Distributed Acoustic Sensing (DAS) has measurements for every meter, which provides new aspects such as in situ measurements during cement jobs and drilling. Other applications of the new fiber optic technology are monitoring of gas migration, source of sustained casing pressure and other measurements which have the potential to develop into standard procedures or even regulatory requirements. With gas migration, corrosion and other changes affecting the integrity of the well construction, integrity can be re-modelled and updated automatically in a fully digital workflow to understand the safety margins. A part of this digital process is automating the risk level for each well and the entire asset. These processes and the prototype of the automated risk assessment are possible in a fully digital process, where planning and well construction commence with support from modern well planning and integrity software.