Condensate banking is a major issue in the production operations of gas condensate reservoirs. Increase in liquid saturation in the near-wellbore zone due to pressure decline below dew point, decreases well deliverability and the produced condensate-gas ratio (CGR). This paper investigates the effects of condensate banking on the deliverability of hydraulically fractured wells producing from ultralow permeability (0.001 to 0.1 mD) gas condensate reservoirs. Cases where condensate dropout occurs over a large volume of the reservoir, not only near the fracture face, were examined by a detailed numerical reservoir simulation. A commercial compositional simulator with local grid refinement (LGR) around the fracture was used to quantify condensate dropout as a result of reservoir pressure decline and its impact on well productivity index (PI). The effects of gas production rate and reservoir permeability were investigated. Numerical simulation results showed a significant change in fluid compositions and relative permeability to gas over a large reservoir volume due to pressure decline during reservoir depletion. Results further illustrated the complications in understanding the PI evolution of hydraulically fractured wells in "unconventional" gas condensate reservoirs and illustrate how to correctly evaluate fracture performance in such a situation. The findings of our study and novel approach help to more accurately predict post-fracture performance. They provide a better understanding of the hydrocarbon phase change not only near the wellbore and fracture, but also deep in the reservoir, which is critical in unconventional gas condensate reservoirs. The optimization of both fracture spacing in horizontal wells and well spacing for vertical well developments can be achieved by improving the ability of production engineers to generate more realistic predictions of gas and condensate production over time.

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Pore pressure and its relationship with fracture net pressure has been reported qualitatively from both field and experimental observations. From a modeling perspective, the ubiquitously used pseudo 3D (P3D) models that are based on linear elastic fracture mechanics (LEFM) do not include the effect of reservoir depletion (or overpressure). Models that utilize effective stress as propagation criteria with a cohesive zone description, introduce the pore pressure directly into the simulation and hence can potentially capture the effect of pore pressure on fracture propagation. This work investigates the effect of pore pressure on hydraulic fracturing net pressure and geometry using empirical and numerical simulation approaches. We carried out an analysis of more than 400 datafrac injections spanning a wide range of geological ages and depositional environments in order to investigate the relationship between observed net pressure and reservoir pore pressure. The net fracture propagation pressure from the fracture treatment analysis was seen to be correlated with the effective stress in the reservoir. Fracture propagation simulations were performed using a coupled finite element – finite difference fracture simulator. The code uses a cohesive zone model (CZM) to describe fracture propagation. Four different effective stress scenarios were used to study the effect of effective stress on net pressure. The simulation results closely match the empirical relation between net pressure and effective stress as obtained from the analysis of actual frac treatment data. It is observed from the simulations that the magnitude of the effective stress also has an effect on the fracture geometry with a high effective stress leading to wider, shorter and more radial fractures. The derived empirical correlation is hence useful as a fracture design parameter. The datafrac net pressure diagnostics workflow in the pseudo 3D models can incorporate local tip pore pressure as a new pressure matching parameter. The pore pressure effect can thus explain high net pressures routinely observed in frac operations and also as a containment mechanism.@en

Accurate prediction of net hydraulic fracture propagation pressure is often impossible. Under some conditions the pressure drop along the fracture dominates while in other cases the pressure at the tip determines the net pressure. Properly scaled lab tests and modeling indicate that effective stress determines the tip propagation pressure, but this is hard to confirm with field data in specific cases.

We therefore gathered a large data base of fracture treatments from many areas to investigate the correlation between net pressure and effective stress. In order to avoid any spurious effect from fluid friction, tortuosity and height containment we limited the data to relatively small injections with water or linear gel in vertical wells. All treatments were in conventional clastic reservoirs, but over a large range of permeability, rock stiffness and geological age.

The data show a remarkably good correlation between net pressure and effective reservoir stress, with a slope of 0.46. Lower net pressure of 200-300 psi was found in over pressured reservoirs and higher net pressure of about 1500 psi was seen in depleted reservoirs. We checked that this is not due to another underlying parameter, such as modulus or depth, which could explain the correlation. It is concluded that the correlation is due to a true relation between net pressure (controlled by fracture propagation) and effective stress. Simulation of representative treatments with a new model that includes a cohesive zone at the fracture tip shows excellent agreement with the observed correlation, supporting a physical relation.

The relation between net pressure and effective stress in the reservoir can contribute to improved treatment design in green fields and also will aid in understanding fracture height growth, since effective stress will differ between formation layers. Calibrated models will still be important in view of lack of detailed formation knowledge, but a correct description of the physics of fracture propagation, based on effective stress at the tip, will facilitate more accurate model predictions.@en