In order to account for big uncertainties such as well interferences, hydraulic and natural fractures’ properties and matrix properties in shale gas reservoirs, it is paramount to develop a robust and efficient approach for well spacing optimization. In this study, a novel well spacing optimization workflow is proposed and applied to a real shale gas reservoir with two-phase flow, incorporating the systematic analysis of uncertainty reservoir and fracture parameters. One hundred combinations of these uncertainties, considering their interactions, were gathered from assisted history matching solutions, which were calibrated by the actual field production history from the well in the Sichuan Basin. These combinations were used as direct input to the well spacing optimization workflow, and five “wells per section” spacing scenarios were considered, with spacing ranging from 157 m (517 ft) to 472 m (1550 ft). An embedded discrete fracture model was used to efficiently model both hydraulic fractures and complex natural fractures non-intrusively, along with a commercial compositional reservoir simulator. Economic analysis after production simulation was then carried out, by collecting cumulative gas and water production after 20 years. The net present value (NPV) distributions of the different well spacing scenarios were calculated and presented as box-plots with a NPV ranging from 15 to 35 million dollars. It was found that the well spacing that maximizes the project NPV for this study is 236 m (775 ft), with the project NPV ranging from 15 to 35 million dollars and a 50th percentile (P50) value of 25.9 million dollars. In addition, spacings of 189 m (620 ft) and 315 m (1033 ft) can also produce substantial project profits, but are relatively less satisfactory than the 236 m (775 ft) case when comparing the P25, P50 and P75 values. The results obtained from this study provide key insights into the field pilot design of well spacing in shale gas reservoirs with complex natural fractures.
Shale field developmentfinds significant challenges when operators have to define optimal spacing of infill wells and further fracture optimization, based on biased understanding of the physical phenomena behind fluid flow in complex unconventional reservoir systems. Although proper modeling has been employed in other studiesto address the detrimental impact of well interference, this study poses how these fracture hits can be beneficial after estimating their impacts in hydrocarbon cumulative recoveries. This study includes spatial variations in fracture conductivity and complexity on fracture geometries of inter-well interference. Furthermore, a non-intrusive embedded discrete fracture model (EDFM) method has been employed to generate these complex scenarios and investigate the impact of well interference multi-well field models. Based on a robust understanding of fracture properties, real production data and wellbore image logging, multiple comparison are performed to address the effects of accounting for inter-well fracture hits on field pressure and production response. First, according to updated production data from Eagle Ford, a model was constructed to perform two (parent) wells history matching. Later, three child wells were included so thatoptimal cluster spacing was recommended considering interwell interference and the distance to thoselong-induced fracture hits. Finally, a field case is presented where the effects of long interwell fractures are evaluated in a nine-well numerical model and contrasted to a scenario without fracture hits. This case is an extension of the work presented by Fiallos et al. (2019) where fracture diagnostic results from well image logging were employed to perform sensitivity analysis on attributes of long interwell connecting fractures. The simulation results show that long induced fracture hits can be addressed by correlating inter-well wellbore image logs, which will support the occurrence of well interference. Because of these interwell long fracture hits, favorable communication is originated and, thereby, it enhances the oil recovery of the child wells by expanding their drainage influence towards further zones of the reservoir. Likewise, the higher permeabilities in this fracture hits reduce the bottomhole pressure drawdown. As a consequence, the model became a valuable stencil to decide the cluster spacing, and to optimize the hydraulic fracture treatment design. The simulation results were applied to the field successfully to afford significant reductions in offset frac interference by up to 50%.
A robust and reliable workflow for well spacing optimization in shale reservoirs development incorporating various types of uncertainties and detailed economics analysis is paramount to achieve a sustainable unconventional production. In this study, we show a novel well spacing optimization workflow based on the results of assisted history matching and apply it to a real shale gas well, incorporating uncertainty parameters such as matrix permeability, matrix porosity, fracture half-length, fracture height, fracture width, fracture conductivity and fracture water saturation. The input ranges of these parameters are 10 nd to 1000 nd, 0.038 to 0.083, 200 ft to 780 ft, 25 ft to 65 ft, 0.1 ft to 4 ft, 10 md-ft to 200 md-ft, and 0.5 to 0.9 respectively and are determined from field experience and exisiting information. Results from assisted history matching are gathered with a total of 60 HM (history matching) solutions out of 325 runs that meets the criteria of BHP (bottomhole pressure) error less than 25% and WGR (water gas ratio) error less than 60%. A total of 1548 proxy solutions out of 100,000 samplings are obtained from MCMC (markov chain monte carlo) algorithm. Embedded discrete fracture model (EDFM) is used to model hydraulic fractures along with a commercial reservoir simulator. The use of greatly facilitates the modelling process of hydraulic fractures compared to the LGR (local grid refinement) method. The uncertainty parameter distributions from our workflow is matching the posterior distribution obtained from assisted history matching. It is found out that the optimal well spacing is approximately 885 ft, with an estimated net present value (NPV) of 6.67 million dollars. Economic uncertainty evaluation is performed and it is discovered that the NPV distribution obtained from the history matching solution is more concave than the results obtained from KNN (k-nearest neighbor) proxy prediction. The optimal well spacing of 885 ft obtained from this workflow is matching closely with the field experience of approximately 1000 ft. The P50 of the NPV distributions of five spacing (1550 ft, 1033 ft, 775 ft, 620 ft, and 517 ft) are 4.04, 5.91, 7.35, 6.42, and 5.44 million dollars respectively. Gas estimated ultimate recovery per well (P50) for the abovementioned spacings are 3070, 3020, 2945, 2750, and 2565 million cubic feet respectively. There is a drastic drop of gas estimated ultimate recovery per well about 6.6% going from a spacing of 775 ft to 620 ft, indicating the onset of well interference between these distances’ range. The practicality and the convenience of our workflow make it possible to be applied to any shale gas well.
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