The Impact of Extended-Time Proppant Conductivity Impairment on the Ultimate Recovery from Unconventional Horizontal Well Completions

The stimulation design of hydraulically fractured wells has always pitted the engineer's capability to maximize the fracture extent (or fracture half-length within the formation) versus the conductivity of the fracture pack generated by the deposited proppant material. In essence, the area of productive reservoir rock contacted by the hydraulic fracture treatment needs to be appropriately engineered to remain connected to the wellbore over the life of the well to maximize reservoir recovery. The completion design of multi-stage hydraulically fractured horizontal wells has been driven by their application to unconventional oil and gas reservoirs. This has primarily occurred in North America where most of the wells drilled and completed were operated by small, private, or upstream-only independent public companies. Metrics used to evaluate performance and completion design changes were short-term in nature and typically focused on parameters such as peak-month production, 90- or 180-day cumulative production; or at longest, the first year or two of cumulative production. Capital efficiency, and capital return or well payout were drivers of value creation in an environment where the well inventory was viewed as extensive if not unlimited and the quick recycling of invested capital created the illusion of value creation. Short-term performance metrics give credence to fracture designs that value most the early-time production that is dominated by rate acceleration. The work presented in this paper shows a comparison of fracture designs in deep unconventional formations looking to minimize cost by pumping all sand proppants versus a focus on ultimate recovery from the reservoir with designs that are more applicable to the stress regime. The work shows the importance of maintaining the wellbore connectivity to the reservoir by designing fracture treatments using proppant conductivity decline data measured over an extended-time period of months or years to maximize ultimate recovery from the reservoir. This approach will be critical to those E&P companies who view their well inventory or resource base as finite and consequently place a priority on maximizing recovery from the reservoir.

The geosolitonic concept of high output hydrocarbon deposits formation

Based on the well-known results of studies of the ether-geosoliton concept of the growing Earth, the article presents the conclusions that made it possible to propose a model of thermonuclear synthesis of chemical elements that form renewable reserves of developed oil and gas fields. It was revealed that local zones of abnormally high production rates of production wells and, accordingly, large cumulative production at developed fields in Western Siberia are due to the restoration of recoverable reserves due to geosoliton degassing. Therefore, when interpreting the results of geological and geophysical studies, it is necessary to pay attention to the identified geosoliton degassing channels, since in the works of R. M. Bembel and others found that they contributed to the formation of a number of hydrocarbon deposits in Western Siberia. When interpreting the results of geological-geophysical and physicochemical studies of the fields being developed, it is recommended to study the data of the ring high-resolution seismic exploration technology in order to identify unique areas of renewable reserves, which can significantly increase the component yield of hydrocarbon deposits.

AI-Based Well Ranking System for Hydraulic Fracturing Events

We are presenting a new, highly intelligent AI-based ranking system for selecting the most appropriate candidates for well treatment. The system is trained to predict flow rates after hydraulic fracturing (HF) and rank wells by the expected effect of the event with machine learning techniques. We demonstrate a significant effort for preprocessing the available field data to create a dataset for training machine learning (ML) models. The dataset included information about geology, transport and storage properties, depths, oil/liquid rates before fracturing for target and neighboring wells. Each ML model has been trained to predict monthly production of oil and liquid right after fracturing and after flow stabilization. Also, confidence intervals of the prediction have been provided. To study the dynamics of future oil rate decline after HF on a stable regime, we have trained several regression models to make predictions at each future point (6 next months after fracturing). To estimate the effect due to HF, we defined expected production "without fracturing." Typically, wells behave with a stable decline trend of production that is approximated by Arps function. The function is defined before HF, then extrapolated to the period after the event where it shows expected production without fracturing. One may conclude about the effectiveness of HF by calculating areas difference under the extrapolated curve (cumulative production without HF), and ML predicted cumulative production for future six months. Reservoir engineers could calculate these differences for each well and create a ranking list from the highest effect to the lowest. The developed system does this automatically for the required oilfield or its part. Therefore, one may easily define the list of best candidates for HF. Gradient Boosting algorithm has been applied to obtain results. Feature selection and tuning of hyperparameters have been provided with the application of cross-validation technique. To test the developed approach, we have divided the dataset from 8 conventional oil fields at a ratio of four to one. The total dataset included 700+ well interventions. Then we have trained and validated models for flow rate prediction on the major part and tested on the holdout part. For different oil field determination coefficients (R2) and normalized root mean square errors (n-RMSE) for oil rate predictions were around R2=0.8 and n-RMSE=0.35 correspondently. The proposed technique is a new approach for fast, accurate, and objective selection of the candidates for hydraulic fracturing based on real-time state of a field. Such AI-based system could become very handy assistant for reservoir engineer in addition to hydraulic fracturing and hydrodynamic simulators. The presented solution computationally efficient and does not require detailed information about HF design.

Leveraging Acoustic Logging for Identification & Quantification of Induced Fractures

The main objective of the acoustic logging in 15K openhole multistage fracturing completions (OH MSFs) is to identify the fracture initiation points behind pipe and contributing fractures to gas production. The technique will also help to understand the integrity of the OH packers. A well was identified to be a candidate for assessment through such technique. The selected well was one of the early 15K OH MSF completions in the region that was successfully implemented with the goal of hydrocarbon production at sustained commercial rates from a gas formation. The candidate well was drilled horizontally to achieve maximum contact in a tight gas sandstone formation. Similar wells in the region have seen many challenges of formation breakdown due to high formation stresses. The objective of this work is to use the acoustic data to better characterize fracture properties. The deployment of acoustic log technology can provide information of fractures initiation, contribution for the production and the reliability of the isolation packers between the stages. The candidate well was completed with five stages open-hole fracturing completion. As the well is in an open hole environment, a typical PLT survey provides the contribution of individual port in the cumulative production but provides limited or no information of contributing fractures behind the pipe. The technique of acoustic logging helped to determine the fracture initiation points in different stages. If fractures can be characterized more accurately, then flow paths and flow behaviors in the reservoir can be better delineated. The use of acoustic logging has helped to better understand the factors influencing fracture initiation in tight gas sandstone reservoirs; resulting in a better understanding of fractures density and decisions on future openhole length, number of fracturing stages, packers and frac ports placement.

RESERVOIR PERFORMANCE ANALYSIS USING MATERIAL BALANCE METHOD IN GAS FIELD

The RF reservoir is a dry gas reservoir located in Northeast java offshore that has been produced since 2018. The RF reservoir has produced 2 wells with cumulative production until December 2019 is 31.83 BSCF. In January 2018 the gas production rate from the two wells was 36 MMSCFD and the reservoir pressure at the beginning of production was 2449.5 psia, peak production occurred in April 2019 with a gas flow rate of 98 MMSCFD but in December 2019 the gas production rate from both wells decreased to 30 MMSCFD with reservoir pressure decreased to 1607.8 psia. Changes in gas flow rate and pressure in the RF reservoir will affect changes in reservoir performance, so it is necessary to analyze reservoir performance to determine reservoir performance in the future with the material balance method. Based on the results the initial gas in place (IGIP) is 80.08 BSCF. The drive mechanism worked on the RF reservoir until December 2019 was a depletion drive with a recovery factor up to 88% and a current recovery factor (CRF) is 40%. The remaining gas reserves in December 2019 is 39 BSCF and the reservoir will be made a production prediction until December 2032. Based on production predictions of the four scenarios, scenario 2 was chosen as the best scenario to develop the RF reservoir with a cumulative production is 66.1 BSCF and a recovery factor of 82.6%.

Optimization of the Hemispherical Solar Distiller Performance Augmented by Different Basin Materials (steel, zinc, and copper) and Reflective Mirrors

The present comprehensive study aims to solve the problem of declining drinking water productivity from solar distillers. The hemispherical distillers are characterized by having the large condensing and receiving surface area, so the utilization of basin materials with high thermal conductivity and reflective mirrors are very effective to enhance a cumulative production of hemispherical distillation. To get the optimal basin materials with the reflective mirror that achieves the highest hemispherical distiller’s performance, three high thermal conductivity basin materials (steel, zinc, and copper) with reflective mirror were tested at the same conditions and compared to reference hemispherical unit. To realize this idea, four distillers was fabricated and tested at a same climate condition namely: Hemispherical solar Distiller with Black Silicone Walls (HSD-BSW), Hemispherical Solar Distiller with Steel Plate and Reflective Mirror (HSD-SPRM), Hemispherical Solar Distiller with Zinc Plate and Reflective Mirror (HSD-ZPRM), and Hemispherical Solar Distiller with Copper Plate and Reflective Mirror (HSD-CPRM). The experimental results presented that the utilization of copper basin materials and reflective mirror (HSD-CPRM) represents the good option to achieve the highest performance of hemispherical distiller, use the copper basin materials and reflective mirror (HSD-CPRM) gives a cumulative production reached 9500 mL/m2 day with improvement of 104.3% compared to reference hemispherical distiller (HSD-BSW). Also, use the copper basin materials and reflective mirror (HSD-CPRM) improves the daily thermal efficiency and exergy efficiency by 102.4% and 194.9%, respectively compared to HSD-BSW. The comprehensive economic analysis concluded that the use of copper basin materials and reflective mirrors (HSD-CPRM) reduced the distillate water cost per liter by 44.1% compared to HSD-BSW.

Evaluation Method of the Vertical Well Hydraulic Fracturing Effect Based on Production Data

Hydraulic fracturing technology has become a key technology for the development of low-permeability/tight oil and gas reservoirs. The evaluation on the postfracturing effect is imperative to the formulation and implementation of the fracturing and development plan. Based on the characteristics of the flow in fracture network after a large-scale hydraulic fracturing, a numerical method for evaluating the effect of fracturing in vertical well was established. This study conducts postfracturing effect evaluations to block C Oilfield’s wells that underwent conventional fracturing and volumetric fracturing, respectively, proposes the definition of fracture network conductivity and its relationship with cumulative production, and analyzes the fracturing construction parameters. The results suggest that the conventional fracturing can only form a single fracture instead of a stimulated reservoir volume (SRV) region. However, the volumetric fracturing transformation can form a complex fracture network system and SRV region and meanwhile bring obvious increase in the production. The effective time lasts for a longer period, and the increase of average daily oil is 2.2 times more than that of conventional fracturing. Additionally, with the progress of the production, the SRV area within the core region of the volume transformation gradually decreased from 6664.84 m2 to 4414.45 m2; the SRV area of the outer region decreased from 7913.5 m2 to 5391.3 m2. As the progress develops, the equivalent permeability and the area of the fracture gradually decrease as the fracturing effect gradually weakens, and so does the conductivity of the network decreasing exponentially; a good correlation is observed between the conductivity of the fracture network, the cumulative production, and fracturing construction parameters, which can serve as the evaluation parameters for the fracturing effects and the basis for fracturing productivity prediction and provide a guidance for fracturing optimization design.

Analyzing the Impacts of Meshing and Grid Alignment in Dual-Porosity Dual-Permeability Upscaling

Summary The discrete fracture network (DFN) model is widely used to simulate and represent the complex fractures occurring over multiple length scales. However, computational constraints often necessitate that these DFN models be upscaled into a dual-porositydual-permeability (DPDK) model and discretized over a corner-point grid system, which is still commonly implemented in many commercial simulation packages. Many analytical upscaling techniques are applicable, provided that the fracture density is high, but this condition generally does not hold in most unconventional reservoir settings. A particular undesirable outcome is that connectivity between neighboring fracture cells could be erroneously removed if the fracture plane connecting the two cells is not aligned along the meshing direction. In this work, we propose a novel scheme to detect such misalignments and to adjust the DPDK fracture parameters locally, such that the proper fracture connectivity can be restored. A search subroutine is implemented to identify any diagonally adjacent cells of which the connectivity has been erroneously removed during the upscaling step. A correction scheme is implemented to facilitate a local adjustment to the shape factors in the vicinity of these two cells while ensuring the local fracture intensity remains unaffected. The results are assessed in terms of the stimulated reservoir volume calculations, and the sensitivity to fracture intensity is analyzed. The method is tested on a set of tight oil models constructed based on the Bakken Formation. Simulation results of the corrected, upscaled models are closer to those of DFN simulations. There is a noticeable improvement in the production after restoring the connectivity between those previously disconnected cells. The difference is most significant in cases with medium DFN density, where more fracture cells become disconnected after upscaling (this is also when most analytical upscaling techniques are no longer valid); in some 2D cases, up to a 22% difference in cumulative production is recorded. Ignoring the impacts of mesh discretization could result in an unintended reduction in the simulated fracture connectivity and a considerable underestimation of the cumulative production.

Application Investigation of Light Proppant in Hydraulic Fracturing of Marcellus Shale

Slickwater-sand fracturing design is widely employed in Marcellus shale. The slickwater- sand creates long skinny fractures and maximizes the stimulated reservoir volume (SRV). However, due to the fast settling of sand in the water, lots of upper and deeper areas are not sufficiently propped. Reducing sand size can lead to insufficient fracture conductivity. This study proposes to use three candidate ultra-lightweight proppants ULWPs to enhance the fractured well performance in unconventional reservoirs. In step 1, the current sand pumping design is input into an in-house P3D fracture propagation simulator to estimate the fracture geometry and proppant concentrations. Next, the distribution of proppant concentration converts to conductivity and then to fracture permeability. In the third step, the fracture permeability from the second step is input into a reservoir simulator to predict the cumulative production for history matching and calibration. In step 4, the three ULWPs are used to replace the sand in the frac simulator to get new frac geometry and conductivity distribution and then import them in reservoir model for production evaluation. Before this study, the three ULWPs have already been tested in the lab to obtain their long-term conductivities under in-situ stress conditions. The conductivity distribution and production performance are analyzed and investigated. The induced fracture size and location of the produced layer for the current target well play a fundamental effect on ultra-light proppant productivity. The average conductivity of ULWPs with mesh 40/70 is larger and symmetric along the fracture except for a few places. However, ULWPs with mesh 100 generates low average conductivity and create a peak conductivity in limited areas. The ULW-3 tends to have less cumulative production compared with the other ULWPs. For this Marcellus Shale study, the advantages of ultra-lightweight proppant are restricted and reduced because the upward fracture height growth is enormous. And with the presence of the hydrocarbon layer is at the bottom of the fracture, making a large proportion of ULWPs occupies areas that are not productive places. The current study provides a guidance for operators in Marcellus Shale to determine (1) If the ULWP can benefit the current shale well treated by sand, (2) what type of ULWP should be used, and (3) given a certain type of ULWP, what is the optimum pumping schedule and staging/perforating design to maximize the well productivity. The similar workflow can be expanded to evaluate the economic potential of different ULWPs in any other unconventional field.

Development of Production-Forecasting Model Based on the Characteristics of Production Decline Analysis Using the Reservoir and Hydraulic Fracture Parameters in Montney Shale Gas Reservoir, Canada

This study developed a production-forecasting model to replace the numerical simulation and the decline curve analysis using reservoir and hydraulic fracture data in Montney shale gas reservoir, Canada. A shale-gas production curve can be generated if some of the decline parameters such as a peak rate, a decline rate, and a decline exponent are properly estimated based on reservoir and hydraulic fracturing parameters. The production-forecasting model was developed to estimate five decline parameters of a modified hyperbolic decline by using significant reservoir and hydraulic fracture parameters which are derived through the simulation experiments designed by design of experiments and statistical analysis: (1) initial peak rate ( P hyp ), (2) hyperbolic decline rate ( D hyp ), (3) hyperbolic decline exponent ( b hyp ), (4) transition time ( T transition ), and (5) exponential decline rate ( D exp ). Total eight reservoir and hydraulic fracture parameters were selected as significant parameters on five decline parameters from the results of multivariate analysis of variance among 11 reservoir and hydraulic fracture parameters. The models based on the significant parameters had high predicted R 2 values on the cumulative production. The validation results on the 1-, 5-, 10-, and 30-year cumulative production data obtained by the simulation showed a good agreement: R 2 > 0.89 . The developed production-forecasting model can be also applied for the history matching. The mean absolute percentage error on history matching was 5.28% and 6.23% for the forecasting model and numerical simulator, respectively. Therefore, the results from this study can be applied to substitute numerical simulations for the shale reservoirs which have similar properties with the Montney shale gas reservoir.