Abstract
Unconventional reservoirs, shale gas and oil for instance, have proven to be an important contributor to hydrocarbon production in North America. Horizontal wells with multiple transverse fractures unlocked these unconventional resources by attaining profitable production rates and increasing gas reserves for future years. A critical challenge in these types of reservoirs is characterizing the stimulated reservoir volume (SRV), by estimating the effective productive volume created during stimulation and quantifying the permeability of the formation.
Recent approaches for rate and pressure data deconvolution have emphasized the benefits of using buildup responses acquired whenever the well is shut-in, often for operational reasons, to assess significant insights about heterogeneity and compartmentalization in conventional reservoirs. However, deconvolution performs poorly when the initial reservoir pressure is unknown and might generate ambiguous results when pressure data accuracy is questionable.
Regular measurements of daily production rates and wellhead flowing pressures can provide important information about well completion, stimulation, and formation parameters. With effective data processing, rate-normalized pressure (RNP) converts variable-rate and variable-pressure data to an equivalent of the drawdown pressure response to constant-rate production. This reveals flow regimes that enable direct estimation of the formation permeability and the productive fracture extent in the SRV. Subsequently, observed field rates and pressures can be matched with a global model to refine the estimates from the flow regime analysis. Although numerical models can be used to match the data, in this study we employed an analytical flow regime equations that provides fast and accurate results that can be easily programmed.
The proposed methodology was applied to production data from Barnett shale wells providing excellent results and demonstrating an efficient, fast, and cost effective method to estimate critical well and formation parameters in unconventional reservoirs. The same methodology can be used to diagnose wells from other unconventional resources.
