Stuart Alan Cox

Evaluation of Long-Term Performance of Oil Wells in Elm Coulee Field

Unconventional oil reservoirs, such as Bakken, have gained considerable interest in recent years because they have become a great resource to produce oil and gas to meet the energy needs of North America. Performance prediction from these tight reservoirs is a challenge because of the complexity of reservoir flow, well completion, and fracture stimulation techniques. Elm Coulee field, in Bakken, is an example of such unconventional reservoirs and is located in Richland County, Montana. The field was drilled using both vertical and horizontal wells, but in recent years the use of horizontal wells has become the standard practice. The objectives of this study were: (1) evaluate the long-term (7 to 10 years) performance of horizontal wells in Montana Elm Coulee, (2) develop a better understanding of how to predict the long-term performance of younger Bakken fields in North Dakota based on the Elm Coulee experience. Arps hyperbolic decline curve analysis was used as the main forecasting approach. In Arps analysis, ( ) ( ) 1/ 1 , b i i q t q bD t − = + where q is the flow rate, D is the decline rate, and b is the decline exponent. It will be demonstrated that forecasts using a constant b overpredicts well performance. To match the long-term performance of Elm Coulee wells, the numerical value of b had to be decreased with time. Analytical approaches (log-log type-curve diagnostic plots and the Fetkovich log-log normalized plot) were also used to decipher the flow regimes, and to determine the varying decline rate from long-term producing wells in Elm Coulee Field. In addition to analytical modeling, numerical modeling was also used because it is more comprehensive in utilizing a larger set of reservoir parameters such as reservoir heterogeneity variations. This is very useful in transferring what we learned from the long-term performance of Elm Coulee Montana wells to the short-term performance of wells in North Dakota by addressing both geology and reservoir property differences between these fields. Introduction Arps decline curve analysis has been extensively used to estimate reserves from depletion drive oil and gas reservoirs since the 1950s. The method utilizes the rate equation, ( ) ( ) 1/ 1 b i i q t q bD t − = + , where q is the flow rate, D is the decline rate given by dt q d D ln − = , and ( ) 1 / b d D dt = . It can be shown that b aq D = where b is a number between zero and one for hyperbolic decline, b equal to zero represents exponential decline and b equal to one is harmonic decline. It will be demonstrated that forecasts using a constant b , obtained from the early transient flow, overpredicts well performance for wells that have long transient flow periods. To match the long-term performance of Elm Coulee wells, the numerical value of b had to be decreased with increasing time. A theoretical reason in support of this action is given below: Yousef et al (2006) presented an analytical-numerical solution of a capacitance model to infer interwell connectivity from well rate data. Their method should work effectively for high connectivity conventional reservoirs. Nonetheless, the capacitance model can be used in low permeability, depletion-type, unconventional reservoirs, to explain why the hyperbolic decline 2 CSUG/SPE SPE 149273 exponent does not remain constant and why it decreases with time. This simple concept is consistent with field observations of production rate decline in Elm Coulee field as reported in this paper. We start with the following equations: ( ) ( ) w p p J t q − = (1) ( ) t p V c t q R t ∂ ∂ = − φ (2) where, ( ) t q is production rate, J productivity or well index, p average pressure in the drainage volume of the well, w p bottom-hole well pressure, R V drainage volume of the well, t c φ specific storage coefficient, and t time. For analytical solution to the capacitance model, J and R V are assumed constant while w p can be either constant or varying with time. When bottomhole pressure is variable, the solution involves a convolution integral. This solution can be used to explain why flowrate can increase with lowering of the bottom-hole pressure. For constant J , R V and w p , the solution of Eqs. 1 and 2 is the exponential decline of flowrate versus time (Yousef, et al, 2006). ( ) ( ) ( ) τ o t t o e t q t q − − = (3)

Errors Introduced by Multiphase Flow Correlations on Production Analysis

First and foremost, production analysis techniques require accurate rate and bottomhole pressure histories. In most cases the pressure history of the well is not measured directly at the bottomhole condition, but is calculated from surface measurements by the use of single or multiphase flow correlations. In some cases significant error is introduced through the use of these correlations. This paper evaluates the magnitude of such errors for oil and gas producers with regard to the estimation of flow capacity, completion efficiency, and effective drainage area. Synthetic cases are used as control sets in order to evaluate the sensitivity of the results to the various multiphase flow correlations and flowing conditions. In addition to synthetic (simulated) performance behavior, field cases are presented and the variance in estimated reservoir and completion properties is evaluated. The technical contributions of this paper are: a. Systematic evaluation of the effect of errors in flow rates and bottomhole flowing pressures on production data analysis — using both synthetic and field derived well performance data. b. Qualitative guidelines as the effect of errors in rate and pressure on estimated reservoir properties. c. Establishment of the most relevant pressure drop correlations for use in practice.