Advanced Modeling Capability to Enhance Near-Wellbore and Far-Field Bridging in Acid Fracturing Field Treatments

SPE/IATMI Asia Pacific Oil &Amp; Gas Conference and Exhibition

Usova

Yudin

2021

Multiple near-wellbore diverters and their applications exist in the industry. However, understanding of their effectiveness in carbonate acid fracturing applications still has unanswered questions, mainly due to the lack of knowledge on how the fracture width develops at entry points with continuous acid dissolution. This continuum needs to be understood through integrated modeling and experimentation at the yard-scale, and field-scale perspectives. An advanced numerical model was used to analyze the width development in varying calcite/dolomite fractions and acid concentrations. A robust diversion pill was developed during extensive testing, and its performance was validated in the laboratory using a slot test. The goal was to create a system with reliable bridging ability and low permeability to ensure isolation. Multimodal particles help to ensure effective bridging and plug stability. A similar bridging test was conducted at the yard scale with a small pump and low-pressure line setup leading to an 8-mm inside diameter pipe. Results from the laboratory were validated in the yard test to see parameters affecting the bridging. Finally, a well-specific robust workflow was constructed for diversion pill design. Modeling done on a high-resolution fracture hydrodynamics and in-situ kinetics model showed that width development in different scenarios varied from 1.5 to 3.0 mm. Laboratory testing was performed in 0.31- to 063-inch width rectangular slots to normalize the flow rate/area of the cross section, and the plug experienced pressure up to 1,200 psi for several hours at temperatures from 115 to 205°F. No extrusion was observed during the test, which is a valid indicator of plug stability. Sensitivity to flow conditions and carrier fluid properties were estimated. The diversion slurry was mixed in a 0.5 wt% solution of guar gum and displaced at pump rates 100 to 999 ml/min. A yard test was designed to see the bridging of the pill at various concentrations of 75 to 300 lbm/1,000 gal and rates of 0.5 to 3 gal/min. All the laboratory- and yard-scale experimental findings were combined with field case studies to understand fracture bridging for dynamic diversion applications. A workflow using modeling and advanced volumetrics design was devised to enhance the diversion success in field applications. This led to formulating a parametric design measure β, which showed direct correlation and effectiveness on the diversion process. This study gives a 360° solution-based understanding of diversion physics. The proposed combination of mechanical and chemical diversion is a cost-effective method for multistage fracturing. Current comprehensive research involving digitized cores and advanced modeling has significant potential to make this a reliable method to develop tight carbonate formations around the globe.

Integrated Workflow with Experimentation, Modeling, and Field Implementation Framework Enhances Fracture Diversion Understanding in Carbonate Reservoirs

SPE/IATMI Asia Pacific Oil &Amp; Gas Conference and Exhibition

Usova

Yudin

2021

Control Over the Fracture in Carbonate Reservoirs as a Result of an Integrated Digital Stimulation Approach to Core Testing and Modeling

Yudin

Day 2 Wed, October 13, 2021

Романовский

et al. 2021

The oilfield industry is rapidly changing towards reduced CO2 emissions and sustainability. Although hydrocarbons are expected to remain the leading source for global energy, costs to produce them may become prohibitive unless new breakthrough in technology is established. Fortunately, the digital revolution in the IT industry continues at an accelerating pace. A digital stimulation approach for tight formations is presented, using the achievements of one industry to solve the challenges of another. The fracture hydrodynamics and in-situ kinetics model is incorporated in the advanced simulator together with the detailed multiphysics models based on acid systems digitization, including rheology and fluid- carbonate interactions data obtained from the laboratory experiments. Digitization of fluid-rock interaction and fluid leakoff was performed using a coreflooding setup that allowed pumping concentrated acids in core samples at high-pressure/high-temperature (HP/HT) conditions. Varying the testing parameters across a broad range allowed refining the model coefficients in the simulator to obtain high accuracy in the predicted results. The digital slot concept was used to validate physical models in an iterative experimental approach. The software proved efficient at providing validation of multiphysics models used together with advanced slurry transport in the simulator. The fine computational grid allowed accurate predictions of the fracture geometry, etched width, and channel conductivity, resulting in realistic well productivity anticipations. Since multiple fluid systems of the acid stimulation portfolio were digitized and incorporated into the simulator, it was possible to optimize complex acid fracturing designs in the real field operations that included retarded single-phase and multiphase acid systems, self-diverting viscoelastic acids, and fiber- based diverting systems. Several case studies from multiple areas and reservoirs from Caspian and Middle East areas have demonstrated extremely positive oil and gas production results with reduced acid volumes with the digital stimulation workflow compared to conventionally stimulated offset wells. The digital stimulation workflow brings a new approach to acid fracturing optimization based on an integrated cycle in which high-resolution data from several sources are processed by powerful computing capacities. Starting from digitizing acid reactions with the core samples, through digitized rheology and particle transport in multiphysics models, an advanced numerical simulator tailors an optimum design from a number of acid system options, pumping rates, additive concentrations, and stage volumes to achieve best geometry of etched channels inside a fracture.

Fracture Height Prediction Model Utilizing Openhole Logs, Mechanical Models, and Temperature Cooldown Analysis with Machine Learning Algorithms

Day 3 Wed, November 17, 2021

BinZiad

Subaii

et al. 2021

Vertical wells require diagnostic techniques after minifrac pumping to interpret fracture height growth. This interpretation provides vital input to hydraulic fracturing redesign workflows. The temperature log is the most widely used technique to determine fracture height through cooldown analysis. A data science approach is proposed to leverage available measurements, automate the interpretation process, and enhance operational efficiency while keeping confidence in the fracturing design. Data from 55 wells were ingested to establish proof of concept.The selected geomechanical rock texture parameters were based on the fracturing theory of net-pressure-controlled height growth. Interpreted fracture height from input temperature cooldown analysis was merged with the structured dataset. The dataset was constructed at a high vertical depth of resolution of 0.5 to 1 ft. Openhole log data such as gamma-ray and bulk density helped to characterize the rock type, and calculated mechanical properties from acoustic logs such as in-situ stress and Young's modulus characterize the fracture geometry development. Moreover, injection rate, volume, and net pressure during the calibration treatment affect the fracture height growth. A machine learning (ML) workflow was applied to multiple openhole log parameters, which were integrated with minifrac calibration parameters along with the varying depth of the reservoir. The 55 wells datasets with a cumulative 120,000 rows were divided into training and testing with a ratio of 80:20. A comparative algorithm study was conducted on the test set with nine algorithms, and CatBoost showed the best results with an RMSE of 4.13 followed by Random Forest with 4.25. CatBoost models utilize both categorical and numerical data. Stress, gamma-ray, and bulk density parameters affected the fracture height analyzed from the post-fracturing temperature logs. Following successful implementation in the pilot phase, the model can be extended to horizontal wells to validate predictions from commercial simulators where stress calculations were unreliable or where stress did not entirely reflect changes in rock type. By coupling the geometry measurement technology with data analysis, a useful automated model was successfully developed to enhance operational efficiency without compromising any part of the workflow. The advanced algorithm can be used in any field where precise fracture placement of a hydraulic fracture contributes directly to production potential. Also, the model can play a critical role in cube development to optimize lateral landing and lateral density for exploration fields.