Statistical & Numerical Density Derivatives Application in Oil and Gas Well Test Interpretation

PhD Thesis


Biu, TV (2016). Statistical & Numerical Density Derivatives Application in Oil and Gas Well Test Interpretation. PhD Thesis London South Bank University School of Engineering https://doi.org/10.18744/PUB.001862
AuthorsBiu, TV
TypePhD Thesis
Abstract

Traditional transient well test analysis has been largely based on draw down solution, which
works for the reservoir engineering problems of isothermal, uniform and single phase flow in
porous media. After so many years of efforts on multi-phase flow approach, methods such as
pseudo-pressure approach has been limited. Numerical well testing approach for multi-phase
flow problems is the only method currently under further investigation.
Presented in this study are three analytical approaches. (1) Statistical pressure derivative
which utilises the 2nd differencing of pressure and time series since pressure change and
subsurface flow rate are non stationary series, then integrates the residual of its 1st
differences using simple statistical functions such as sum of square error SSE, standard
deviation, moving average MA and covariance of these series to formulate the model. (2)
Pressure-density equivalent algorithm for each fluid phase, which is derived from the
fundamental pressure-density relationship and its derivatives used for diagnosing flow
regimes and calculating permeability. (3) Density transient analytical DTA solution derived
with the same assumptions as (2) above, but the density derivatives for each fluid phase are
used along with the semi-log density versus time plot to derive permeability for each fluid
phase. (2) and (3) are solutions for multi-phase flow problems when the fluid density is
treated as a function of pressure with slight change in density.
The first method demonstrated that for high water production well, a good radial stabilization
can be identified for good permeability estimation without smoothing the data. Also it
showed that in cases investigated, the drawdown fingerprint can be replicated in the build-up
pressure response, hence a good match of the data and a better radial flow diagnosis.
The second and third methods can, not only derived each individual phase permeability, the
derivative response from each phase is visualised to give much clearer picture of the true
reservoir response, which in return ensures that the derived permeability originates from the formation radial flow. These approaches were tested with synthetic and field data. The
synthetic studies demonstrated that the calculated numerical density derivatives on the
diagnostic plot yield much clearer reservoir radial flow regime and give more confident
formation permeability estimation. The study also discovered that in the cases investigated,
the heavier the fluid such as water, the better permeability estimation from the weighted
average pressure-density equivalent derivatives.
In order to support further field application of this approach, field data sets were identified
and analysed using the developed methods. In this case, the conventional pressure derivative
diagnostic method failed to identify the radial flow, hence unable to estimate the reservoir
permeability. In contrast, the three methods: statistical pressure, fluid phase numerical
density and pressure-density equivalent derivatives gave very clear radial flow stabilizations
on the diagnostic plot, from which the reservoir permeability was derived, which matched
the up scaled core permeability from the same formation. The presented approaches provide
an estimation of the individual fluid phase and formation effective permeabilities, reflecting
the contribution of each phase to flow at a given point.

Year2016
PublisherLondon South Bank University
Digital Object Identifier (DOI)https://doi.org/10.18744/PUB.001862
Publication dates
Print01 Oct 2016
Publication process dates
Deposited23 Feb 2018
Publisher's version
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https://openresearch.lsbu.ac.uk/item/8720q

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