Analysis of flowrate fluctuations for reservoir communications

Turning production 'noise' into reservoir flowpath information

Reactivated structural features are likely to be major influences on the hydraulic flow paths in the reservoir and therefore their identification is of substantial advantage to efficiency in reservoir management. Recent research, in partnership with The University of Edinburgh, has developed a methodology for extracting inter-well communications from the correlations in rate between wells.

What value is added?

Whilst much is generally known about reservoir properties at well locations, the communications between wells are arguably more important to reservoir performance, particularly in flooding schemes. Conventionally, interwell properties are either inter-/extra-polated geostatistically from well data; or measured with tracers (only informative after breakthrough of injected fluid), or expensive geophysical surveys (e.g. 4D seismic); even where measurements have been made, there is generally inherent uncertainty in interpretation. The extraction of interwell communications from readily available production data using our technology can complement and enhance the understanding of reservoir behaviour. Various potential entry points exist for applications of the results in the processes of operational reservoir management. Rate correlations can be compared with other known structural knowledge of the field to indicate potential features that may have been activated by field development. Such features might be introduced into a conventional reservoir simulation as increased permeability or, better, used as calibration or validation of a geomechanical model. The updated reservoir simulation, preferably coupled to the geomechanical model, can then be used for improved predictions of short- or long-term production.

What is it about?

Analysing the statistics of the history of production and injection flowrate fluctuations at wells in a field to examine the influence of faults, fractures and their geomechanical changes. The statistical analysis initially uses standard correlation measures, but is then followed by novel techniques to refine the interpretation. The concept of geomechanical influence is shown in the cartoon alongside:

What we deliver

1) Statistically confident correlations in flowrates between each pair of wells indicating reservoir communications; plus a map showing those faults which appear to be most influencing the correlations, inferred to be geomechanically active faults, and therefore potentially conduits to flow (see maps alongside for previous examples).

2) Rate diffusivities: by examining the time and spatial behaviour of correlations in rates, a 2d diffusivity tensor can be extracted. These are defined for each of the Delauney triangles between well locations. Since the assumption of conventional reservoir simulation is that fluid flow is diffusive, this is a more practical tool for assistance in calibrating (history-matching) reservoir models. Rate diffusivities are not the same as hydraulic diffusivities but intuitively there is likely to be a strong degree of correspondence.

The figure to the right shows the major axes (black lines) of the rate diffusivity tensors derived from the raw rate histories of a field. They are superimposed upon shear strains at the end of modelling time from the VISAGETM (Schlumberger) coupled model of the field depletion. Colour values are representative of the degree of normal shear on sub-vertical faults or fractures (hot colours: high; cold colours: low). modelled show high values in similar locations, implying diffusivities are derived from faults and fractures activated in normal shear. The high values around the periphery of the field might be realised in the field as shear on sub-vertical faults or fractures.

What data do we need? Simply:

- the usual monthly oil, gas, water production (and injection if in operation) volumes per well from field start-up to present-day.


- a list of well bottom-hole locations (e.g. utm co-ordinates),

- average formation volume factors for oil, gas & water.

- Fault maps and stress data against which to compare our interpretations could be supplied with the rate data or left to a later stage.

Timescale: delivery of results ~3 weeks after receipt of data

Most recent reference: SPE 154429 (Europec/EAGE June 2012)


This technology was developed in a series of research projects, in partnership with The University of Edinburgh: it began as parts of NERC CONNECT grant GR3/C0022 with matching funding from BP, and continued as part of the COFFERS project, under the Industry Technology Facilitator Complex Reservoirs Programme, and under the RESURGE project, which was supported by a grant from the United Kingdom Technology Strategy Board. We are grateful to sponsors: Amerada Hess, BG Group, BP, Conoco-Phillips, DTI, Kerr-McGee, Statoil, Shell and Total, who supported the work by providing funds, data or robust and constructive criticism. The Technology Strategy Board's role is to promote and support research into, and development and exploitation of, technology and innovation for the benefit of UK business, in order to increase economic growth and improve the quality of life.