Automated pressure transient analysis: A cloud-based approach

Highlights

• A novel cloud-based approach allows pressure falloff analysis (PTA) to be conducted automatically.

• The automated PTA analysis approach significantly reduces analysis time and cost.

• The automated PTA analysis provides consistent results that are independent of the analyzer's experience and knowledge.

• The automated PTA analysis represents an optimal way to overcome big data challenges facing by oil/gas industry.

Abstract

Pressure transient analysis provides essential information to evaluate the dimensions of injection induced fractures, permeability damage near the wellbore, and pressure elevation in the injection horizon. For injection wells, shut-in data can be collected and analyzed after each injection cycle to evaluate the well injectivity and predict the well longevity. However, any interactive analysis of the pressure data could be subjective and time-consuming. In this study a novel cloud-based approach to automatically analyzing pressure data is presented, which aims to improve the reliability and efficiency of pressure transient analysis.

There are two fundamental requirements for automated pressure transient analysis: 1) Pressure data needs to be automatically retrieved from field sites and fed to the analyzer; 2) The engineer can automatically select instantaneous shut-in pressure (ISIP), identify flow regimes, and determine the fracture closure point if any. To meet these requirements as well as to take advantage of cloud storage and computing technologies, a web-based application has been developed to pull real time injection data from any field sites and push it to a cloud database. A built-in pressure transient workflow has been also proposed to detect any stored or real-time pressure data and perform pressure analysis automatically if the required data is available.

The automated pressure transient analysis technology has been applied to multiple injection projects. In general, the analysis results including formation and fracture properties (i.e. permeability, fracture half length, skin factor, and fracture closure pressure) are comparable to results from interactive analysis. Any discrepancies are mainly caused by poor data quality. Issues such as inconsistent selections of ISIP and different slopes defined for pre and after closure analyses also contribute to the divergence. Overall, the automated pressure transient analysis provides consistent results as the exact same criteria are applied to the pressure data, and analysis results are independent of the analyzer's experience and knowledge.

As data from oil/gas industry increases exponentially over time, automated data transmission, storage, analysis and access are becoming necessary to maximize the value of the data and reduce operation cost. The automated pressure transient analysis presented here demonstrates that cloud storage and computing combined with automated analysis tools is a viable way to overcome big data challenges faced by oil/gas industry professionals.