Eagle Ford Shale completions evaluation

Completions evaluation analysis provides a mechanism to better calibrate and build underlying geomechanical and reservoir models, improving forecasting of fracture placement and production and helping to accelerate optimization of future wells and treatment designs.

The fracture created during hydraulic stimulation can greatly deviate from the planar bi-wing textbook example and may be more accurately represented by a complex network of fractures instead.

Microseismic data and source mechanisms will constrain not only the location of fractures but also their geometry and orientation in space, resulting in a discrete fracture network (DFN) that serves as an important input for reservoir simulation and from which the total rock volume that was affected by the treatment can be calculated.

FIGURE 1. In the microseismic data for wells A and B, events are colored by their respective source mechanism and sized by magnitude. (Source: MicroSeismic Inc.)

This can then be further refined by placing proppant in the DFN to help discern between the part of the stimulated rock volume (SRV) that is expected to contribute to production in the long term and the part of the SRV that showed microseismic activity but might not contain hydraulically connected features or fractures.

Dataset

The study dataset was acquired with a temporary surface array for a two-lateral well pad completed in the Eagle Ford Shale for Murphy Oil. The array consisted of 10 arms and 1,200 channels with six geophones per channel.

The processing that is employed is similar to conventional 3-D seismic processing. The high-fold, wide-azimuth and large-aperture geometry of the monitoring array provides a consistent imaging resolution under the entire array and provides a high-confidence estimate of event magnitude. Another advantage is the capability to determine source mechanisms, a crucial input for the analysis presented in this case study. The broad areal coverage records the polarity changes of the seismic wavefront as it arrives at the surface, which can be inverted to obtain the strike, dip and rake of the associated failure plane.

Figure 1 shows that two types of source mechanisms were observed. While induced fracture-related failure was recorded in a dip-slip mechanism, indicating that the maximum principal stress is vertical, a prestressed, pre-existing feature was observed in the south-southeast/north-northwest direction failing in strike-slip mode, indicating that the maximum principal stress is horizontal.

FIGURE 2. In the M-DFN for wells A and B, fracture orientation is calibrated on event source mechanism. Fracture geometry is calibrated on event magnitude, rock rigidity and injected fluid volume. (Source: MicroSeismic Inc.)

Magnitude-calibrated DFN

To distinguish between the total SRV where microseismic activity was observed and the part of the SRV that contains proppant-filled fractures and will therefore be productive in the long term, a magnitude-calibrated DFN (M-DFN) is modeled onto the microseismic events. Through source mechanism analysis, strike and dip of the failure plane are identified for each individual event. The geometry of each individual failure plane is then determined through the magnitude of an event incorporating rock and fluid properties, resulting in the M-DFN shown in Figure 2. From the moment magnitude, the seismic moment can be calculated, which depends on the area of the failure plane, the displacement along the plane and the rigidity of the rock. Assuming that the total detected seismicity is directly related to the injected fluid volume and that the change in volume is completely accommodated by the seismic failure minus leak-off, the calculated fracture volume should equal the injected fluid volume. Since the seismic energy that was recorded during a treatment and subsequently located as discrete events is usually only a fraction of the total emitted energy, the two volumes described above rarely match. To account for any undetected microseismic event population such as tensile failure or microseismic events with a signal below the detection threshold, a scaling factor is introduced. Each variable defining the geometry of the fracture is then recalculated so that the fracture volume matches the effective injected fluid volume.

Proppant placement and propped SRV

Estimating the propped half-length is performed by filling the M-DFN with proppant from the wellbore outward on a stage-by-stage basis. Proppant filling is constrained by allowing only a fraction of the proppant to populate fractures intersecting the prevalent failure plane azimuth at high angles. The fracture volume inside the respective stage M-DFN is filled with proppant until all proppant that was pumped is accounted for to obtain the proppant-filled fractures of the total M-DFN, as seen in Figure 3. Estimated propped half-lengths are then determined in a wellbore-centric coordinate system by breaking up the proppant-filled fracture distances into a perpendicular horizontal, a parallel horizontal and a perpendicular vertical component with respect to the corresponding stage center.

FIGURE 3. This image shows the proppant-filled M-DFN for wells A and B. (Source: MicroSeismic Inc.)

To calculate the total SRV, a 3-D grid is applied to the total M-DFN. The total SRV is dependent on the size of the model cells and can be adjusted based on known reservoir flow properties. It represents the total rock volume that was affected by the treatment. To discern between the part of the SRV that is assumed to be drained over the lifetime of the wellbore and the remaining part of the SRV, the grid is applied to the proppant filled M-DFN as well. The subset SRV that is calculated from the part of the M-DFN containing proppant then represents the propped SRV that is expected to contribute to production in the long term, as illustrated in Figure 4.

Completion design, vertical coverage

Comparable to the wellbore spacing analysis, an ideal stage length and spacing can be determined by measuring the longitudinal extent of the propped fracture network as well as analyzing the longitudinal fracture growth with the injected fluid volume. The numbers obtained from both techniques indicated an average overlap of 26% between stages, toward the previously treated stage as well as toward the next stage. Further analysis of the microseismic data, however, showed that most overlap occurs close to the wellbore. Therefore, stage spacing and overall length may be decreased for increased connectivity and complexity of the fracture network and more uniform drainage along the lateral.

While the majority of the microseismic activity was contained within the lower Eagle Ford, substantial upward growth into the upper Eagle Ford was observed. Both wells showed fairly symmetrical upward and downward growth, indicating consistent treatment of the target zone as well as some treatment of the hydrocarbon-bearing sections of the Eagle Ford above the target depth.

FIGURE 4. In the total SRV and propped SRV for wells A and B, total SRV can be seen on the left side, and propped SRV can be seen on the right side. The propped SRV represents the part of the microseismically active rock volume that is related to proppant-filled fractures and therefore long-term production. (Source: MicroSeismic Inc.)

Acknowledgment
The authors would like to thank Murphy Oil Corp. for generously agreeing to publish the findings of this study.