Wellbore storage removal in pressure transient analysis for gas wells

Third Author's Department

Petroleum & Energy Engineering Department

Find in your Library

https://doi.org/10.1016/j.petrol.2021.109712

Document Type

Research Article

Publication Title

Journal of Petroleum Science and Engineering

Publication Date

1-1-2022

doi

10.1016/j.petrol.2021.109712

Abstract

Wellbore storage (WBS) occurs due to fluid loading/unloading in the wellbore, when a well starts production or is shut-in. This phenomenon creates variable sandface rate and time lag between the surface production rate and the stable sandface rate. Wellbore storage effects can sometimes conceal important information and complicate well test analysis and interpretation. In well tests that suffer from long WBS, removal of WBS effects can usually recover important features in the reservoir signal and lead to significant improvement in identifying the reservoir model and calculating reservoir parameters. Until recently, WBS removal relied on direct deconvolution techniques that require accurate well test data. Presence of noise in the pressure and rate data usually makes direct deconvolution methods unstable. Well test pressure and rate data usually suffer from some noise, and therefore, application of direct deconvolution methods may not work. This work develops a stable technique to eliminate WBS effects present in gas wells. The technique uses two deconvolution steps and applies the recently developed deconvolution algorithms (e.g. von Schroeter algorithm) for stable computations. Unlike the direct deconvolution methods (which become largely unstable when minor noise is present in data) in WBS removal, the proposed approach also extends the reservoir signal over both the drawdown and buildup periods. The new technique is applied to simulated gas well test data in a variety of conditions for validation. The applications considered different well/reservoir models and included different levels of data noise. The technique is also applied to a field case to show the value of the proposed approach. The findings of this study can be used to eliminate WBS effects and recover reservoir signal. It has applications in variety of gas reservoirs where WBS can hide information such as low permeability reservoirs, natural fractured reservoirs, small reservoirs, and wells with large wellbore volume. The reservoir properties calculated from reservoirs after removal of WBS can be used in further calculations such as estimates of gas in place and well productivity to help engineers optimize their wells/reservoirs performance.

This document is currently not available here.

Find this item online

Share

COinS