Production Analysis Case Study

Read this journal article. The study uses production analysis to develop a robust workflow and help in designing sustainable shale production. Figure 2 depicts an initial production analysis. What would an organization need to collect production parameters?

Introduction

Initial production analysis

The first step in data analysis is to convert the surface readings to bottom-hole values. This was achieved by uploading the well configurations along with the fluid properties and the production history to the well performance simulator PROSPER. Subsequently, the normalized rate versus the normalized material balance time was plotted to identify the flow regimes. Material balance pseudo-time (t_mb) can be calculated using Eq. (2):

$t_{\mathrm{mb}}=\frac{\mu_{i} C_{t i}}{q} \int_{0}^{t} \frac{q}{\bar{\mu} \bar{C}_{t}} \mathrm{~d} t$ (2)

where μ is the gas viscosity, C_t is the total compressibility, and q is the gas flow rate. The calculated pseudo-time is normalized to obtain the maximum material balance time (MBT). The rate is divided by pseudo-pressure (P_P) calculated using Eq. (3).

$p_{p}=\frac{\mu_{i}}{\rho_{i}} \int_{p_{i}}^{p} \frac{\rho}{\mu} \mathrm{d} p$ (3)

where ρ is the gas density. By dividing the rate by p_p, the highest normalized rate is obtained. Two flow regimes, namely bilinear flow, and linear flow were clearly identified with no sign of transition to boundary dominated flow (BDF) (Fig. 3). The bilinear flow attributed to fracture cleanup, lasted for 2 months, recovering about 13.5% of the fracturing fluid pumped into the reservoir during the fracturing operations. Subsequently, the stabilization of the gas/water ratio (GWR) was observed producing 50 bbl/MMscf of gas, indicating that the well cleanup period has ended. As only a linear flow exists, the minimum SRV and the maximum SRV permeability can also be estimated.

Fig. 3

Normalized gas production rate versus material balance time (log–log scale)

Next, the normalized gas production rate versus the square root of the gas production time was used to estimate the product of the fracture half-length and the square root of permeability

$\left(x_{f} \sqrt{k}\right)$ (Fig. 4 ). The slope of the straight line in Fig. 4 is

$30 \mathrm{mD}^{0.5 \mathrm{ft}}$ and it is the product

$x_{f} \sqrt{k}$ , according to Eq. 1. Also, Eq. 4 defines the maximum SRV permeability using the time of the end of linear flow and fracture spacing. Finally, the minimum SRV was estimated by extrapolation in the flowing material balance time plot (Fig. 5).

Fig. 4

Square root time plot versus normalized gas rate

Fig. 5

Flowing material balance plot

$k=\frac{1896 \phi C_{t} d_{i}^{2}}{t_{\text {elf }}}$ (4)

The trilinear composite model was used to model production utilizing the input data extracted from straight-line analysis. The rectangular model with 45 equally spaced fractures was also used to model production. Initial completion parameters and the estimations of the straight-line analysis are used as initial input for the model, and regression of inner permeability, fracture half-length, and fracture conductivity was performed. The predictions of the model provided an excellent match with the production history as shown in Fig. 6.

Fig. 6

Well production history match