Rate & pressure vs. time (Cartesian) plot

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Examine the rate & pressure vs. time (Cartesian) plot to answer the following questions:

Do step changes in pressure and rate correlate with each other?

  • A sharp increase in rate should correspond to a sharp decrease in pressure, and vice versa.
  • The response to a step change should be immediate and not gradual.

Reasons for inconsistencies:

Incorrect pressure

  • The pressure may have been measured on the other side of the choke / valve.
  • A change in liquid holdup in the wellbore.
  • At high drawdown, the rate becomes insensitive to pressure changes. For additional information, see the percentage drawdown plot. If changes in pressure are not reflected in the rate data, this may not be a cause for concern.
  • Pressures may be measured every minute, but reported daily. An average daily rate is meaningful, but an average daily pressure is not.
Incorrect rate
  • The rate may be averaged from group metering.
  • The rate may be a daily or monthly average.
  • Unreported liquid production from a gas well.

Time periods

  • If the data in different time periods is inconsistent, the data in the low-flow-rate region is more likely to be in error.

Is the general trend in the rate reflected in the pressure, and vice versa?

  • If the rate is disrupted but comes back to the original trend, the pressure should also return to its original trend.
  • If there is a change in the rate trend, the change in the pressure trend should be consistent with these bulleted items.)

Reasons for inconsistencies:

  • A change in operations (for example, location of pressure measurement, metering, etc.).
  • Tubing change-outs, hydraulic fractures, work-overs, recompletions, etc. The Blasingame, NPI, FMB rate, and FMB pressure plots tend to be better suited for this diagnosis.

Is the production rate and pressure data stable?

  • Unstable rates indicate slugging, even though no water is reported.
  • Sometimes rates are smoothed by reporting an average day rate.
  • Sometimes pressure data is smoothed for supervisory control and data acquisition (SCADA) systems.
  • These smoothing actions obscure fluctuations.

Reasons for inconsistencies:

  • Liquid production may only be measured at the plant, and not at the well.
  • Often water production is not properly reported.
  • Liquid loading in the wellbore.
  • The WGR & water rate plot provides further insight.
  • The Turner rate plot is a valuable diagnostic tool.
  • Sandface pressures can fluctuate, even though wellhead pressures are smooth. This is due to the multiphase calculations of sandface pressures.

Is the rate and pressure data smooth, continuous, and free of scatter?

  • Outliers can create a false unit slope (which suggests boundary-dominated flow) on typecurves that use the concept of "material balance time".
  • Interpolation of missing pressures is often misleading.
  • If the reported data appears too smooth, it is possible that interpolations are used, instead of measurements.

Reasons for inconsistencies:

  • Pressure and rate data often contain outliers. This scatter can be removed from the production dataset using a median filter.
  • Sometimes failing to exclude these outliers can result in false conclusions about the reservoir, because they tend to line up on a unit slope on a typecurve log-log plot. For additional information, see the Blasingame plot.
  • These outliers can be recognized because they are sparse.
  • Linear interpolation or averaging of pressures is not a true representation of reservoir characteristics.
  • The rule of thumb is that if the data appears too straight, it is most likely incorrect, not measured, or interpolated.