Well Spacing and Stimulation Design Optimization in the Vaca Muerta Shale: Hydraulic Fracture Simulations on the Cloud

2021 ◽  
Author(s):  
Sahil Malhotra ◽  
Alejandro Lerza ◽  
Sergio Cuervo
Keyword(s):  
Cloud Computing ◽  
Hydraulic Fracture ◽  
Fracture Network ◽  
Simulation Methods ◽  
Development Cost ◽  
Fracture Simulation ◽  
Well Spacing ◽  
Design Variables ◽  
Vaca Muerta ◽  
Discrete Fracture

Abstract Well spacing and stimulation design are amongst the highest impact design variables which can dictate the economics of an unconventional development. The objective of this paper is to showcase a numerical simulation workflow, with emphasis on the hydraulic fracture simulation methodology, which optimizes well spacing and completion design simultaneously. The workflow is deployed using Cloud Computing functionality, a step-change over past simulation methods. Workflow showcased in this paper covers the whole cycle of 1) petrophysical and geomechanical modeling, 2) hydraulic fracture simulations and 3) reservoir simulation modeling, followed by 4) design optimization using advanced non-linear methods. The focus of this paper is to discuss the hydraulic fracture simulation methods which are an integral part of this workflow. The workflow is deployed on a dataset from a multi-well pad completed in late 2018 targeting two landing zones in the Vaca Muerta shale play. On calibrated petrophysical and geomechanical model, hydraulic fracture simulations are conducted to map the stimulated rock around the wellbores. Finely gridded base model is utilized to capture the property variation between layers to estimate fracture height. The 3d discrete fracture network (DFN) built for the acreage is utilized to pick the natural fracture characteristics of the layers intersected by the wellbores. The methodology highlights advances over the past modeling approaches by including the variation of discrete fracture network between layers. The hydraulic fracture model in conjunction with reservoir flow simulation is used for history matching the production data. On the history matched model, a design of experiments (DOE) simulation study is conducted to quantify the impact of a wide range of well spacing and stimulation design variables. These simulations are facilitated by the recent deployments of cloud computing. Cloud computing allows parallel running of hundreds of hydraulic fracturing and reservoir simulations, thereby allowing testing of many combinations of stimulation deigns and well spacing and reducing the effective run time from 3 months on a local machine to 1 week on the cloud. Output from the parallel simulations are fitted with a proxy model to finally select the well spacing and stimulation design variables that offer the minimum unit development cost i.e. capital cost-$ per EUR-bbl. The workflow illustrates that stimulation design and well spacing are interlinked to each other and need to be optimized simultaneously to maximize the economics of an unconventional asset. Using the workflow, the team identified development designs which increase EUR of a development area by 50-100% and reduce the unit development cost ($/bbl-EUR) by 10-30%.

Microseismicity-constrained discrete fracture network models for stimulated reservoir simulation

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. B37-B47 ◽  
Author(s):  
Sherilyn Williams-Stroud ◽  
Chet Ozgen ◽  
Randall L. Billingsley
Keyword(s):  
Hydraulic Fracture ◽  
Fracture Network ◽  
Discrete Fracture Network ◽  
Three Dimensions ◽  
Fracture Flow ◽  
Signal To Noise ◽  
Discrete Fracture ◽  
Microseismic Events ◽  
The Impact ◽  
Dfn Model

The effectiveness of hydraulic fracture stimulation in low-permeability reservoirs was evaluated by mapping microseismic events related to rock fracturing. The geometry of stage by stage event point sets were used to infer fracture orientation, particularly in the case where events line up along an azimuth, or have a planar distribution in three dimensions. Locations of microseismic events may have a higher degree of uncertainty when there is a low signal-to-noise ratio (either due to low magnitude or to propagation effects). Low signal-to-noise events are not as accurately located in the reservoir, or may fall below the detectability limit, so that the extent of fracture stimulated reservoir may be underestimated. In the Bakken Formation of the Williston Basin, we combined geologic analysis with process-based and stochastic fracture modeling to build multiple possible discrete fracture network (DFN) model realizations. We then integrated the geologic model with production data and numerical simulation to evaluate the impact on estimated ultimate recovery (EUR). We tested assumptions used to create the DFN model to determine their impact on dynamic calibration of the simulation model, and their impact on predictions of EUR. Comparison of simulation results, using fracture flow properties generated from two different calibrated DFN scenarios, showed a 16% difference in amount of oil ultimately produced from the well. The amount of produced water was strongly impacted by the geometry of the DFN model. The character of the DFN significantly impacts the relative amounts of fluids produced. Monitoring water cut with production can validate the appropriate DFN scenario, and provide critical information for the optimal method for well production. The results indicated that simulation of enhanced permeability using induced microseismicity to constrain a fracture flow property model is an effective way to evaluate the performance of reservoirs stimulated by hydraulic fracture treatments.

Closing the Gap in Characterizing the Parent Child Effect for Unconventional Reservoirs - A Case of Study in Vaca Muerta Shale Formation

2021 ◽  
Author(s):  
Alejandro Lerza ◽  
Sergio Cuervo ◽  
Sahil Malhotra
Keyword(s):  
Hydraulic Fracture ◽  
Production Performance ◽  
Drainage Area ◽  
Real Field ◽  
Well Spacing ◽  
Fracture Development ◽  
Vaca Muerta ◽  
Pressure Depletion ◽  
The Impact ◽  
Parent Child

Abstract In Shale and Tight, the term "Parent-Child effect" refers to the impact the depleted area and corresponding stress changes originated by the production of a previously drilled well, the "parent", has over the generated hydraulic fracture geometry, conforming initial drainage area and consequent production performance of a new neighbor well, called "child". Such effect might be considered analogous to the no flow boundary created when the drainage areas of two wells meet at a certain distance from them in conventional reservoirs; but, unconventional developments exhibit higher exposure to a more impactful version of this phenomena, given their characteristic tighter well spacing and the effect pressure depletion of the nearby area by the neighbor well has over the child well's hydraulic fracture development. Due to the importance the Parent-Child effect has for unconventional developments, this study aims first to generally characterize this effect and then quantify its expected specific project impact based on real field data from the Vaca Muerta formation. To do so, we developed a methodology where fracture and reservoir simulation were applied for calibrating a base model using field observed data such as microseismic, tracers, daily production data and well head pressure measurements. The calibrated model was then coupled with a geomechanical reservoir simulator and used to predict pressure and stress tensor profiles across different depletion times. On these different resulting scenarios, child wells were hydraulically fractured with varying well spacing and completion designs. Finally, the Expected Ultimate Recovery (EUR) impact versus well spacing and the parent´s production time were built for different child´s completion design alternatives, analyzed and contrasted against previously field observed data. Results obtained from the characterization work suggests the parent child effect is generated by a combination of initial drainage area changes and stress magnitude and direction changes, which are both dependent of the pressure depletion from the parent well. Furthermore, the results show how the well spacing and parent's production timing, as well as parent's and child's completion design, significantly affect the magnitude of the expected parent child effect impact over the child's EUR.

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