Abstract

Using available data from existing wells to plan new wells is standard practice in development of unconventional natural gas resources. However, available data may frequently contain hidden patterns that are not easily spotted. Uncovering such patterns could help provide guidance for new wells by answering questions such as the following: Which wells, for which data are available, behave similarly? What do similarly behaving wells have in common? How can this information be used for new wells? If some existing wells are known not to perform satisfactorily, what are the underlying reasons? How can poor performance be avoided in new wells?

In this work, we are proposing an approach addressing these questions. Production data from multiple wells are supplied to principal component analysis (PCA) data pool. The so-called scores and loadings associated with principal components (PCs) are computed, and subsequent comparison of PCs can be used to reveal clusters of similarly behaving wells and their underlying distinguishing features. The data is further explored by estimating decline curve parameters using power-law exponential decline curve q(t)=Qiexp(D^itn). Once production data from multiple wells are available, values of the parameters q^i,D^i,n are estimated for each well and then correlations between available well and formation parameters such as permeability, fracture conductivity, fracture half-length, aspect ratio, drainage area, zone thickness and cumulative gas in place in drainage area; and decline curve parameters are obtained using partial least square regression (PLSR). These correlations can be used to predict production behavior of new wells if well parameters are known. Moreover, they can guide the location, geometry, and stimulation of new wells.

The proposed analysis was performed on twelve wells from the Holly Branch gas field, for which data were available. The analysis identified one cluster of nine wells behaving similarly, and three distinct wells. The difference between these wells was ascribed mainly to high fracture conductivity, permeability, and small fracture half length. Correlations for decline curve parameters were obtained with reasonable R-squared value.

The proposed methodology can be used as a decision making tool that employs various data from existing wells to guide decisions on the geometry and stimulation of new wells in unconventional gas field development.

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