An Integrated Digital Solution for Well Shut-In Detection and Validation and Reservoir Pressure Estimation

Author:

Soares Cesar1,Adil Mohamed2,Pareek Aditya2,Vashistha Amit2,Shivank Yashaswi2,Dutta Urmi2

Affiliation:

1. XTO Energy Inc.

2. ExxonMobil Services and Technology Private Limited

Abstract

Abstract Shut-ins of production and injection wells are an integral part of annual asset planning to obtain information that is unavailable during production well tests or routine injection operations. Near-wellbore reservoir pressures, productivity and injectivity indices, and skin factors are critical for production, injection and maintenance schedule planning and can be estimated using pressure data observed during well shut-ins. Engineers across different assets often utilize spreadsheet-based tools with custom written macros to acquire and analyze relevant data and to estimate well parameters. These user-developed tools can be field or well-specific and lack generalization for adoption across multiple assets, proving difficult to maintain and lacking proper data archival mechanisms that are crucial to track evolution of well behavior over time. In an effort towards digitalization, a solution that automates identification, validation and archival of well shut-in periods with asset and completion specific rules has been developed. A graphical user interface (GUI) provides visualization of relevant pressure, temperature, rate, and valve position attributes during shut-in periods and enables the necessary user interactivity to analyze shut-in periods. The digital solution integrates application programming interfaces (APIs) to retrieve real-time data from OSISoft PI servers and to store identified shut-in periods and associated attributes in centralized SQL databases. Operating valve positions, rates, and choke openings are tracked to approximate shut-in periods with configurable rules through JSON interfaces. Furthermore, filter convolution is applied on pressure gradient data to fine tune shut-in start and end times. The programmatic methodology leverages valve position trends, in addition to wellhead and downhole pressures and temperatures observed during each recorded shut-in period to facilitate shut-in validation. Dashboards comparing pressure build-ups for producers and pressure falloffs for injectors across different shut-in periods captured during a well's operational history enable engineers to identify potential changes in skin effects, permeability, and wellbore phase redistribution effects. To facilitate estimation of reservoir pressures using build-up/fall-off data, a reservoir pressure estimation method has been implemented with a built-in user interface to update and archive changes in wellbore reference depths and gradients which are vital for depth correction of pressure data. Steady-state detection enforces validation criteria for stable pressure before shut-in and rapid choke ramp-down, augmenting simpler QA/QC rules such as minimum flowing duration between shut-in periods and time taken to reach pressure differential thresholds. The integrated digital solution has been deployed as a web application to several oil-producing assets. The application is expected to aid asset engineers in planning and validating shut-ins, and to standardize extraction and archival of additional wellbore and reservoir information efficiently. This presentation highlights the development of programmatic components for the described methodology and demonstrates an application of the tool to analyze shut-ins for a deepwater field.

Publisher

SPE

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