The present study provides a comprehensive set of new analytical expressions to help understand and quantify well interference due to competition for flow space between the hydraulic fractures of parent and child wells. Determination of the optimum fracture spacing is a key factor to improve the economic performance of unconventional oil and gas resources developed with multi-well pads. Analytical and numerical model results are combined in our study to identify, analyze, and visualize the streamline patterns near hydraulic fractures, using physical parameters that control the flow process, such as matrix permeability, hydraulic fracture dimensions and assuming infinite fracture conductivity. The algorithms provided can quantify the effect of changes in fracture spacing on the production performance of both parent and child wells. All results are based on benchmarked analytical methods which allow for fast computation, making use of Excel-based spreadsheets and Matlab-coded scripts. Such practical tools can support petroleum engineers in the planning of field development operations. The theory is presented with examples of its practical application using field data from parent and child wells in the Eagle Ford shale (Brazos County, East Texas). Based on our improved understanding of the mechanism and intensity of production interference, the fracture spacing (this study) and inter-well spacing (companion study) of multifractured horizontal laterals can be optimized to effectively stimulate the reservoir volume to increase the overall recovery factor and improve the economic performance of unconventional oil and gas properties.
The objective of this study is to visualize the drained rock volume (DRV) and pressure depletion in hydraulically and naturally fractured reservoirs, using a high-resolution simulator to plot streamlines and time-of-flight contours that outline the DRV, based on computationally efficient complex potentials. A recently developed expression based on fast, grid-less Complex Analysis Methods (CAM) is applied to model the flow through discrete natural fractures with variable hydraulic conductivity. The impact of natural fractures on the local development of DRV contours and streamline patterns is analyzed. A sensitivity analysis of various permeability contrasts between natural fractures and the matrix is included. The results show that the DRV near hydraulic fractures is significantly affected by the presence of nearby natural fractures. The DRV location shifts according to the orientations, permeability and the density of the natural fractures. Reservoirs with numerous natural fractures result in highly distorted DRV shapes as compared to reservoirs without any discernable natural fractures. Additionally, the DRV shift due to natural fractures may contribute to enhanced well-interference by flow channeling via the natural fractures, as well as the creation of undrained rock volumes between the natural fractures. Complementary pressure depletion plots for each case show how the local pressure field changes, in a heterogeneous reservoir, due to the presence of natural fractures. The results from this study offer insights on how natural fractures affect the DRV and pressure contour plots. This study uses a fast grid-less and meshless high-resolution flow simulation tool based on CAM to simulate the flow in heterogeneous naturally fractured porous media. The CAM tool provides a practical/efficient simulation platform, complementary to grid-based reservoir simulators.
Data Analytics is progressively gaining traction as a viable resource to improve forecasts and reserve estimations in most prospective US shale plays. Part of those learnings has been tested for the reserves and resources estimation of the next worldwide top-class shale play, Vaca Muerta formation in Argentina. In this work, we rely on advanced artificial intelligence methods to automate workflows for production forecasting and reserve estimation in the Vaca Muerta formation. To achieve this goal, we develop a computational platform capable of integrating several sequential operations into a single automated workflow: (1) data gathering; (2) data preparation; (3) model fitting and forecasting and, (4) EUR estimation. As new data becomes available, each of these steps is performed automatically. The proposed platform also integrates with advanced business intelligence tools that aid at facilitating graphical interpretation and communication among specialists and decision makers. Hence, the suggested workflow can deliver production forecasts several magnitudes faster than traditional workflows while maintaining accurate and engineering sound results. Having fast and reliable forecast turnarounds allow for timely tracking key differences and commonalities among multiple shale plays to facilitate informed decision strategies in unconventional field evaluation and development.
Pola, Jackson (Heriot-Watt University) | Geiger, Sebastian (Heriot-Watt University) | Mackay, Eric (Heriot-Watt University) | Bentley, Mark (Heriot-Watt University) | Maier, Christine (Heriot-Watt University) | Al-Rudaini, Ali (Heriot-Watt University)
We investigate how efficiently oil can be recovered from a carbonate rock during surfactant based enhanced oil recovery (EOR) at the core-scale, particularly when chemical processes change wettability, and analyse how geological heterogeneities, observed at the next larger scale (centimetre to decimetre) impacts the effectiveness of surfactant-based EOR at the inter-well scale.
To quantify how heterogeneity across scales impacts surfactant flooding, we combine laboratory experiments with simulation studies at the core- and inter-well scale. We first analysed a series of surfactant imbibition experiments at different surfactant concentrations (from 0 to 3 wt. %) using reservoir cores from the Wakamuk field, a carbonate reservoir in Indonesia. We then built a 3D simulation model of the laboratory experiment and matched the experimental data to identify the key physical mechanisms (e.g., reduction in interfacial tension (IFT) and wettability alteration) that lead to increased oil recovery. Next, we parametrised the surfactant models using assisted history-matching methods to calibrate the relative permeability and capillary pressure curves as a function of surfactant concentration. These models were then deployed in high-resolution simulations at the inter-well scale. These simulations captured the small-scale geological heterogeneities that are typical for a carbonate reservoir system, e.g., the Shuaiba formation in the Middle East, but are not resolved in field-scale models.
Our core-scale simulations demonstrate a change from co- to counter-current flow in the laboratory experiments and indicate that the resulting increase in oil recovery is due to a combination of IFT reduction, wettability alteration from oil- to water-wet, and capillary pressure restoration; these processes need to be captured adequately at the inter-well scale model. The increase in surfactant concentration above the critical micelle concentration (CMC) (i.e., from 1 to 3 wt. %) triggered the capillary pressure restoration and dominated recovery at the early-time. The changes in relative permeability and capillary curves during the surfactant floods were best modelled using a concentration-based interpolation. There is uncertainty when calibrating surfactant models using laboratory experiments. A key question hence is if geological heterogeneity at the inter-well scale masks these uncertainties.
Results from our high-resolution simulations show that large-scale heterogeneity impacts recovery predictions, but it is the coarsening of the grid, not the upscaling of permeability, that dominates the error in field-scale recovery predictions during surfactant based EOR. Indeed, the error arising from numerical dispersion during grid coarsening can be as large as the error arising when selecting an inaccurately configured surfactant model due to the lack of quality experimental data. Hence appropriate grid refinement, possibly using adaptive grid refinement, needs to be considered when setting up a surfactant based EOR simulation, along with the appropriate configuration of the surfactant model itself.
Using planar fracture models to match treatment pressure and improve understanding of the fracture geometry generation is not a new concept. Knowledge gained from this exercise has historically been used to improve engineered fracture completions and production, and maximize net present value (NPV); however, at some point during the progression from vertical to horizontal wellbores, many within the industry have forgotten about the learnings that can still be gained from current fracture models. Engineered completions have been largely replaced by spreadsheet efficiencies relevant to operations rather than production in too many cases. Some images of unconventional well stimulation treatments portray fractures growing in every direction, forming patterns that resemble shattered windshields, and have often excluded the known physics related to rock geomechanics, reservoir properties, and geology. Excuses to dismiss modeling are numerous and are gaining the reasoning of conformists.
Unconventional resource plays might or might not contain large numbers of natural fractures; but, current fracture models can still be used to gain insight into the fracture geometries being generated. While the development of complex fracture models continues to evolve, the industry can still gain insight to fracture geometry and resulting production using current planar fracture modeling. Caveats to this process are that it requires: Valid measured data to establish model constraints. The engineer to understand the basic physics of how fractures are generated and when (and when not) to twist the "knobs" in the model. The engineer to understand which "knobs" should be used based on real diagnostics information. The actual single well production to be an integral part of the process.
Valid measured data to establish model constraints.
The engineer to understand the basic physics of how fractures are generated and when (and when not) to twist the "knobs" in the model.
The engineer to understand which "knobs" should be used based on real diagnostics information.
The actual single well production to be an integral part of the process.
This paper demonstrates the results of honoring data measurements from a multitude of potential sources, including downhole microseismic data, downhole deformation tiltmeters, offset pressure monitoring, DTS, DAS, diagnostic fracture injection test (DFIT) analysis, injection as well as production data with bottomhole pressure measurements, etc., and the resulting observations and conclusions. Several industry examples are discussed to help frame the vast amount of information possible to help engineers do a better job of including more diagnostics into routine operations to provide additional insight and ultimately result in improved models and completion designs.
This paper is not intended to merely demonstrate the results of the work but to spark an interest in bringing more intense engineering back to fracture stimulation modeling for horizontal completions.
Tian, Changbing (Research Institute of Petroleum Exploration and Development, PetroChina) | Lei, Zhengdong (Research Institute of Petroleum Exploration and Development, PetroChina) | Jiang, Qingping (Exploration and Development Research Institute of Xinjiang Oilfield Company) | Chang, Tianquan (Exploration and Development Research Institute of Xinjiang Oilfield Company) | Chen, Dongliang (Exploration and Development Research Institute of Xinjiang Oilfield Company) | Lu, Zhiyuan (Exploration and Development Research Institute of Xinjiang Oilfield Company) | Li, Sheng (Exploration and Development Research Institute of Xinjiang Oilfield Company)
Large platforms, long horizontal sections, small well spacings and dense cutting have become economical and effective development means for tight oil reservoirs. Well spacing and fracture design are critical parameters impacting production and Internal rate of return (IRR) of tight oil reservoirs. In order to maximize the total stimulated reservoir area and fracture-controlled reserves, the well spacing and fracture spacing should be small enough. However, in order to minimize the chance of fracture hits caused by offset wells and the overlapping drainage area of a nearby well to avoid Asset spillover, the spacing well should large enough.
Based on minifrac data and microseismic fracture mapping results, a natural/hydraulic fracture network was generated and input into an unstructured-grid-based discrete fracture reservoir simulation model. Its accuracy was calibrated with the well production history. For each group of fracture design and well spacing, well interference was determined by estimating ultimate recovery (EUR) difference between a single well and a middle well among multiple wells. Based on actual information of tight oil developments, the pressure interference were examined by field trail data and well spacing simulations. The real scenarios were selected to study effects of well spacing on EUR and ultimate IRR. Effects of reservoir permeability and fracture half-length on optimal well spacing were also analyzed.
It was found that the decrease in Long-term EURs for different well spacings is a good indicator for well spacing optimization. Based on the reservoir simulation and economic analysis, the maximum IRR of the tight oil reservoir with permeability of 0.23mD can achieved when the well spacing is 260m. Meanwhile, the detailed results were also illustrated to show the effects of fracture half-length, reservoir permeability as well as oil price variation on IRR.
The paper demonstrates an effective method and a workflow to optimize well spacing and fracture treatments design through integrating advanced multi-stage fracture modeling with discrete fracture reservoir simulation in the area of unconventional resource developments. Such optimization studies contribute to minimize operation cost and improve the economy of resource development.
Production and proved reserves in the Permian Basin’s Wolfcamp Shale and Bone Spring Formation are reaching new heights, and a new assessment from the US Geological Survey indicates the industry is just scratching the subsurface when it comes to what may be technically recoverable. Major oil discoveries by Armstrong Oil & Gas and ConocoPhillips have compelled the US Department of the Interior to reassess its estimate of undiscovered, technically recoverable resources in parts of Alaska. The list of the biggest gas plays in the US is being revised as the US Geological Survey creates new estimates based on additional drilling results and available rock samples. New at Number 2 is the Mancos Shale on the Western Slope of the Rockies with 66 Tcf in recoverable reserves.
A recently launched joint industry project (JIP) is working to improve petrophysical analysis methods to reduce the time and expense of characterizing tight sandstone gas reservoirs for exploration, appraisal, and production. Failure to prioritize objectives and improper selection of candidate wells can have significant implications for both derived value and potential risk. Data mining for production optimization in unconventional reservoirs brings together data from multiple sources with varying levels of aggregation, detail, and quality. A data-driven approach to successfully analyze and evaluate production-fluid impact during facility system divert events is presented. The work flow effectively identifies opportunities for prompt event mitigation and system optimization.
The F field in the Middle East currently has more than 40 producing wells in the center of the structure. The uneven well distribution limits the understanding of 3D reservoir characterization, particularly in the flank areas. A new technique that analyzes scanning electron microscope (SEM) images of formation samples has been used to measure porosity and total organic carbon (TOC) in the Wolfcamp Shale of the Delaware Basin in west Texas.
A Midland Basin case study on estimating production, drainage volume, and interference from multiple stacked wells. Openhole multistage (OHMS) systems are more cost-effective than the cemented casing plug-and-perf (CCPP) techniques for increasing production and reducing development costs. Understanding how much rock is being stimulated and propped is critical for unconventional producers. New imaging methods using electromagnetic energy or acoustic microemitters could represent a milestone in understanding what is left behind after fracturing. The integration of microseismic data with 3D seismic attributes, and well log and completions data is used to understand geomechanical rock properties.