The investigation of the effect of hydration swelling on induced fracture generation and the resulted permeability in shale has considerably expanded in recent years. However, only a few experiments under anisotropic compressive stress conditions have been done in this area. The experiment methodology that was presented in this paper can be used to study the effect of hydration swelling on fracture initiation and propagation, and the change of shale permeability under anisotropic compressive stress conditions. An artificial fracture through a core was created before the test to simulate the hydraulic fracture generated during the fracturing process. Distilled water was used to simulate the hydraulic fracturing fluid. A CT scanner was used to collect the CT images of fracture development. A digital pressure transducer was used to monitor the upstream pressure change, and the downstream pressure was kept at atmosphere pressure. We, for the first time, combined water adsorption, stress anisotropy conditions, and shale permeability change into one test. Five tests were conducted: three tests underwent stress anisotropy, and the other two tests employed stress isotropy. These tests were continuously exposed to working fluids at a constant flow rate. From the results, the increase in the apparent weight of cores showed that water could be adsorbed into shale samples during the tests. In shale samples with stress anisotropy conditions, fractures through the core were generated. More fractures were created under larger differential stress conditions. The upstream pressure decreased when fractures through the core were generated or particle detachment happened. The decrease in pressure indicates that hydration may be beneficial to shale permeability recovery. To differentiate the effect of hydration and stress anisotropy on fracture generation, one sequential imbibition test was conducted (oil, then water). Fractures can be generated if the imbibition fluid changed from oil to water. The results supported the previous result that hydration may induce fractures ( Liu and Sheng, 2019 ). The experimental results show that this methodology is a practical way to study the effect of hydration on shale properties in the process of hydraulic fracturing.

Hydraulic fracturing is the most prominent technique for increasing well productivity in shale oil and gas reservoirs. Spacing between perforation clusters, with Plug-and-Perf (PnP) fracturing method also believed to be spacing of fractures, is one of the parameters that need to be optimized in fracturing design. This work presents an analytical method to optimize fracture spacing based on the assessment of production data from multi-fractured horizontal wells. Five hydraulically fractured horizontal wells completed in a high clay-content shale formation were considered as examples in this study. Based on the theory of pseudo-steady state (PSS) flow, oil well productivity was investigated with special focus on perforation cluster spacing. Wells exhibiting linear flow in rate transient analyses are believed to have a potential of productivity improvement with shorter fracture spacings. Oil productivity potential with closer fracture spacing was identified for wells in the same reservoir. Result of analyses shows that some wells experienced linear transient flow, indicating significant separation between hydraulic fractures. Use of an analytical well productivity model to simulate pseudo-steady production indicates that fracture spacing could have been reduced to improve well productivity. These wells can be considered as candidates for re-fracturing if possible. Future wells to be drilled in the area nearby should be completed with shorter spacing of perforation clusters. Some wells in the case fields do not show linear transient flow, indicating interferences between either hydraulic fractures and/or natural fractures. These wells should not be refractured. New wells near these wells should not be completed with fracture spacing less than the spacing values used in the existing wells.

The major goal to propose the semi-analytical method is to model/simulate hydraulic fracturing process based on closed form solution of a Theory of Elasticity problem. The analysis results for a Single-Fracture case is going to be compared to well-known resolved problem to show the performance of the proposed method. However, for the case of Multi-Fracture, some findings and outcomes are being addressed. Unlike well-known methods such as PKN or KGD, which rely on some simplifying assumptions (such as the elliptical cross-section of the fractures) our proposed method attempts to model and simulate the process numerically in 3D form which is more realistic and versatile. Several numerical methods have been proposed by industry scholars such as BEM and FEM which comprise very complicated numerical integrations and, hence, involve computational resources dramatically. Our proposed method utilizes a closed form Elasticity Problem to reduce the volume of numerical integrations and produce satisfactory results in much less amount of time. The formulation computes displacements and displacement derivatives. After computer codes were designed and developed to implement the proposed semi-analytical Method, which is a simplified form of Boundary Element Method (BEM), the results are compared to a benchmark example previously published in research papers both numerically and graphically. The computer code is capable to analyze pressurized penny-shaped fractures and compute displacement and displacement derivative fields. By acquiring these values in generated grid nodes in the domain, Cauchy strains and stresses can be obtained. By all the stress components at grid nodes, principal stress values and directions, and therefore, maximum shear stress and direction can be computed. After that, the computer code has to be verified and validated by comparison of results and well-known resolved examples. The examples are, but not limited to, Okada problems published in 1985 and 1992. The other Problem is pressurized Penny-Shaped horizontal fracture which is called Fialko Model. The comparisons show the validity of the proposed method. The boundary element formulation in this method is an exact solution and generates exact values for displacements, displacement derivatives and stress fields and does not need numerical integration. However, since hydraulic fractures of any shape and geometry are being discretized by proposed Boundary Element, the final outputs will be approximated results. This method, which is going to be shown, is much faster than other numerical methods.

The ensemble methods show the ability to obtain the geometry of natural fractures in high-permeability reservoirs. However, hydraulic fractures in unconventional reservoirs are different and the ability of these methods to invert production data to determine hydraulic fracture geometry is unknown. In this work, Embedded Discrete Fractures method is selected as the simulation method. The EnKF and EnRML methods are chosen as the history matching methods. Several simulation cases are used to test these algorithms’ performance in both conventional and unconventional reservoirs. Also, a novel gradient history matching process has been proposed to solve part of the problems. By comparing history matching results of different cases, Ensemble methods’ matching quality is very sensitive with prior information. Production of wells in low-permeability reservoirs is not sensitive with the unconnected fractures, which will lead to multiple minima in the objective function. It also causes big difficulties in the estimation of the gradient for ensemble methods. Thus, it is even more important to add prior information properly in the unconventional reservoirs’ history matching, which can narrow the problem dramatically. The potential and limitation of using a gradient method to solve this kind of problem are also shown in this paper.

Current industry trend of "manufacturing" approach to develop unconventional shale reservoirs would make the journey to reach an optimized solution long by considering the historical deployment of current and emerging technologies in the last decade in North America. The basic premise is that " it is not possible to optimize what it is not fully understood ". Significant research and the deployment of multiple technologies by the industry, academia and governments around the world are contributing to improve our understanding of how to develop unconventional shale reservoirs. However, key challenges remain that are fundamental to be addressed to reach an optimized development and it would require a " different mindset " to be able to develop effectively unconventional shale reservoirs. Technologies deployed to develop unconventional shale reservoirs should be subdivided based on two dynamic processes. The first dynamic process is occurring during the hydraulic fracture generation and the second dynamic process is during the production phase. The first dynamic process plays a vital role that influences the second dynamic process. The main scope of this paper is to assess recovery factor distribution and well spacing for a shale oil reservoir considering both dynamic processes. The Current work is based on the utilization of Kinetix-Intersect; modeling results were compared to Stimplan for a selected stage and rate transient analytical results. Highly complex heterogeneous hydraulic fractures are created during the first dynamic process resulting in variable areal and vertical pressure distribution and flow anisotropy occurred during the second dynamic process or production phase. Kinetix-Intersect model results indicated a variable recovery factor distribution after 30 years of production, 8.9% in the near-wellbore dynamic nano-darcy region, 2% and 1.7 % for the inter-hydraulic fracture and external feeder regions respectively for the shale oil producer evaluated. Kinetix-Intersect model results indicated that about 2/3 of total hydrocarbons produced are contributed by the near-wellbore dynamic nano-darcy and inter-hydraulic fracture regions and the remaining 1/3 by the external feeder region. Acknowledging the variability of recovery factor distribution and pressure depletion associated to the producer drainage area should be the basis for the potential implementation of Enhanced Oil Recovery (EOR) techniques. For the shale oil producer analyzed in this study, current model results indicate an asymmetrical shape drainage area and a variable well spacing in the range of 350 to 400 meters based on displacement efficiency and non-uniform recovery factor distribution. From a pressure depletion perspective, the estimated well spacing should be at least 400 meters. However, an optimum full field development would require the consideration to implement variable well spacing and tailoring completion and fracture treatment designs based on timely identification of areal and vertical heterogeneity of static/dynamic reservoir and geomechanical drivers to optimize project economics. Streamlines were used as a drainage qualitative indicator tool to help defining well spacing criteria. In summary, the route to attain better recovery factors for unconventional shale oil reservoirs commence with the understanding and quantification of the areal and vertical pressure depletion distribution along the horizontal section of the parent wells based on both dynamic processes; this is a vital input to define a suitable well spacing and effectively deploy adaptable drilling, completion and fracture treatment designs to reduce the occurrence of detrimental ‘Frac –Hits’ and improve oil recovery for future parent-child wells. The current expected recovery factors for unconventional shale producers are suboptimal with natural depletion and the need to increase the recovery factor with the deployment of EOR technology is paramount.

Completion design is widely considered as a dynamic area of experimentation and development due to its significant impact on production performance in unconventional reservoirs. As the industry moves beyond the paradigm of proppant and base fluid analysis, more and more focus is being given to the composition of chemicals being used in the completion design. This paper focuses on quantifying the true impact of these chemicals used in completion design by using machine learning to solve this multivariable problem and creates value by providing a framework to help completion engineers select the optimum chemicals and aid in fracture treatment design process, using a data-driven approach. Depending on the shale formation being fractured, a typical fracture treatment job uses a very low concentration of 3-12 additive chemicals. This selection is carried out from thousands of commercially available chemicals and is based on treatment job performance carried out during the modeling phase as well as from field experience. In this work the authors have tried to deconstruct the varied chemical groups used in a hydraulic fracturing job, to analyze its impact independently. In order to understand the impact of hydraulic fracturing chemicals on short term (6 month BOE), midterm (12 month BOE) and long term (24 months BOE) productivity, an analysis is performed using feature selection methods like SelectKBest (F Regression score), Tree-based regression, Mutual Info Regression, Recursive Feature Elimination (RFE) and Correlation-based Feature Selection (CFS). In this paper, Max Ingredient Mass (LBS) is utilized for correlation with production to determine if more or fewer quantities should be used in the Powder River Basin. Comprehensive data exploration is carried out to generate correlations between the chemicals and productivity which helps to identify and link multiple causes to effects and weigh the strength of the correlations, which might not be obvious to the naked eye. A comparison of algorithms for three different target variables shows how certain chemicals are significant at the beginning of production and gain/lose their importance with time. The present paper provides in-depth insight into the impact of the most commonly used chemical types in shale completions. It uses machine learning to provide a truly novel understanding of the individual contribution of these products. It adds to the understanding around this concept by developing a cause and effect relationship between chemical design and composition and the impact on production and provides recommendations on process optimization in completion design.

The importance of evaluating and predicting the performance of producers cannot be emphasized too much, and their production performances can directly determine the economic feasibilities. What's more, production data analysis (PDA) can also be used to evaluate the geological information and give us good guidelines to develop the reservoirs. To comprehensively understand the performance of a multiple fractured horizontal well (MFHW) with complex fracture networks, a semi-analytical model for PDA are established to for Junggar Basin shale oil reservoir, based on the previous work (Tang et al. 2019). Furthermore, based on Blasingame type curve, the production performances of a MFHW is studied. To comprehensively understand what parameters can influence the different stages of production period, a series of sensitivity analyses have been done. Finally, we use this new production model to perform a type-curve matching and compare with the interpretation results getting from pressure transient analysis (PTA) method in a case from Junggar Basin, it is found that these two methods get almost the same results, which means that the proposed PDA model is reliable. The results show that production performances of a MFHW with complex fracture networks in a production decline curve can be divided into five flow regimes, including: (1) bilinear flow, (2) fluid support flow, (3) linear flow, (4) crossflow from matrix to natural fracture networks, and (5) radial flow. Results from sensitivity analysis show that with the increase of fracture networks scale, the holistic production rate will increase, and the influence of hydraulic fractures (HFs) are much greater than that of interconnected micro fractures (IMFs). It is also noted that the early period of the production behavior is mainly influenced by the density of the fracture networks while the later production behavior is dominated by the scale of the fracture networks.

The United States hydraulic fracturing and completion activities have seen a paradigm shift in the pumped water and proppant volumes along the increasing completed lateral over time. Hydraulic fracturing has become the most dominant treatment in North America to tap the unconventional resources. Large scale analysis of the completion size in terms of the amount of proppant, water, and lateral length trends over the period of 2011 and 2018 is presented in this paper. The objective of this study is to elucidate the completion trends over time and to summarize the average values of the completion and stimulation parameters. It will put the readers’ mind in perspective of how much proppant and water have been utilized over the years and shine a light on the progression of the industry growing demand on water and proppant. Data from FracFocus website, which serves as an official chemical disclosure registry for many of the oil and gas states, were utilized in this study. For each stimulated well, it reports water volume and mass percentage of proppant and all other chemical ingredients. The raw data were scraped, parsed, and cleaned using advanced statistical and validation approaches to extract useful information out of the noisy data. A database of more than 80,000 wells was built and integrated into this study. Proppant total mass and the concentration of other chemical ingredients were calculated. The obtained new variables were coupled with other completion parameters such as the horizontal length, perforated lateral length, and well types. The data of each parameter were subjected to rigorous quality control and inspected for outliers. After passing all the data quality and validation procedures, an advanced data visualization technique was selected to reflect the trends over time. The overall trends of the whole aggregated United States are presented in this paper. Investigating the created visualizations showed that there is an undeniable increasing trend in the amount of the proppant and water being consumed over the investigated period. This paper exploits a large number of wells and their associated parameters. Such a large dataset will provide a comprehensive and practical representation of the completion and stimulation trends. It will also establish a baseline and reference values for the investigated parameters by benchmarking the mean, median, and other statistical expressions for each time period.

A major outstanding challenge in developing unconventional wells is determining the optimal cluster spacing. The spacing between perforation clusters influences hydraulic fracture geometry, drainage volume, production rates, and the estimated ultimate recovery (EUR) of a well. This paper systematically examines the impact of cluster spacing in the Eagle Ford shale wells by calibrating fracture geometry and fracture/reservoir properties using field injection and production data and evaluating the optimal cluster spacing under different reservoir conditions. We explore a sequential technique to evaluate and optimize cluster spacing using a controlled field test at the Eagle Ford field. This study first identifies the fracture geometry by history matching the field injection treatment pressure. Using the rapid Fast Marching Method based flow simulation and Pareto-based multi-objective history matching, we match the well drainage volume and the cumulative production to calibrate the fracture and SRV properties. The impact of cluster spacing on the EUR are examined using the calibrated models. We run injection and production forecasts for various cluster spacing to investigate optimal completion under different reservoir conditions. The unique set of injection and production data used for this study includes two horizontal wells completed side by side. The well with tighter cluster spacing has larger drainage volume and better production performance. This is because of the increased fracture complexity in spite of the impact of stress shadow effects leading to shorter fractures. The calibrated models suggest that most of the fractures are planar in the Eagle Ford shale. The well with wider cluster spacing tends to develop longer fractures but the well with tighter cluster spacing has better stimulated reservoir volume with enhanced permeability, thus resulting in better drainage volume and production performance. From the optimization runs under different reservoir conditions, our results seem to indicate that when natural fractures are present or when stress anisotropy is high with no natural fractures, the wells with tighter cluster spacing tend to outperform the wells with wider cluster spacing. However, severe stress shadow effect is observed when stress anisotropy is low with no natural fractures, likely making tighter cluster spacing wells less favorable. The calibrated fracture geometries and properties with a unique set of Eagle Ford field data explain the performance variation for completions using different cluster spacing within the reservoir and provides insight into optimal cluster spacing under different reservoir conditions (low vs high stress anisotropy and with/without natural fractures).

Unconventional reservoirs, characterized by their ultra-low permeability and porosity, have complicated production mechanisms yet to be fully understood. Gas produced from unconventional oil reservoirs are majorly classified as the secondary product, with the focus on oil. However, gas plays a vital role in the production of oil from unconventional plays and can be economically beneficial as well. Therefore, while oil production forecasting is highly important, it is equally imperative to figure out ways in which solution gas production can be forecasted. There has been very little information in the literature about forecasting solution gas production. The huge question is - can we possibly forecast gas-oil ratios and ultimately, solution gas production? And if we can, can we do that with some reasonable level of certainty? This paper attempts to answer these questions by exploring the use of an Asymmetrical Sigmoid Model (ASM) to forecast gas-oil ratios (GOR) and solution gas production. Asymmetrical sigmoid functions have been applied in several fields of study such as biology, finance, agriculture, etc. Research into the possibility of employing the use of this type of function for predicting future GOR values, arose from studies and observation of the nature of GOR profiles of wells in unconventional oil reservoirs. This paper presents a new approach to forecasting gas-oil ratios and solution gas production - the Asymmetrical Sigmoid Model (ASM). A commercial compositional reservoir simulator was used to simulate 30 years of production from multi-fractured horizontal wells (MFHW) with different reservoir fluids. Further, ASM was used to forecast producing gas-oil ratios from the wells with production histories ranging from six months to 3 years. The results were compared to simulated GOR data. Solution gas production were then calculated from the estimated producing gas-oil ratios using the trapezoidal rule and compared to simulated solution gas production data as well. This methodology was similarly applied to field data from various wells in different shale oil reservoirs and the results were compared to the available historical field data. In recent years, factors such as limited production data, complex flow mechanisms of liquid-rich shale reservoirs, production pattern of producing gas-oil ratios among others, have made the task of forecasting GOR and solution gas production difficult. However, ASM enables us to have a simple functional approach that empiricallymimicsthe basic pattern of producing GOR profiles in unconventional oil reservoirs quite well. ASM also helps to forecast gas-oil ratios and solution gas production with reasonable measures of accuracy. After the application of ASM to available historical data, and comparing the results with simulated and field data, there were relatively low error percentages in majority of the cases considered. Due to the continuous rise in global demand for energy, and its corresponding economic implications, the importance of research focused on improving and finding new ways of accurately forecasting oil and gas production cannot be downplayed. This work presents aninnovative and easyway offorecasting gas-oil ratios and solution gas production from unconventional oil plays. It is a valuable contribution to the ongoing efforts of research into better and simpler ways of forecasting production from unconventional reservoirs. Findings from this work can help to improve reserves estimation, reservoir management, field development planning and overall project economics.

Hydraulic fracturing in the Marcellus Shale play has moved to produced water only scenarios because of prohibitive water disposal costs. Well completion under produced water only conditions increases the demand on chemical additive performance. In addition, water reuse selects deleterious microorganisms through natural selection, which may increase the likelihood of formation souring. Conventional biocides are typically used to mitigate these risks, but to some extent, they present health, safety, and environmental (HSE) concerns. In addition, several conventional biocides have side reactions with sulfide, notably tetrakis(hydroxymethyl)phosphonium sulfate (THPS) and 2,2-dibromo-3-nitrilopropionamide (DBNPA). This paper describes an improved method for the effective control of deleterious microorganisms without the use of conventional biocides. An environmentally friendly system that includes nitrate-reducing bacteria (NRB) coupled with nitrate co-introduction was previously shown to mitigate souring as effectively as a biocide alternative for more than 1,000 assets. The NRB inhibit growth of the deleterious sulfate-reducing bacteria (SRB) primarily by competing for the available carbon source if the source is limited. This paper describes an improved NRB/nitrate system that incorporates a sulfate analog, which presumably inhibits dissimilatory sulfate reduction and enhances mitigation. Laboratory experiments were performed to measure the amount of hydrogen sulfide (H 2 S) produced in field brine samples inoculated with SRB. The improved NRB/nitrate system was shown to inhibit the production of H 2 S under worst-case scenarios in laboratory competitive exclusion experiments. Results for the new treatment at four trial wells are presented. Sulfate-reducing bacteria populations, acid-reducing bacteria populations, and a gaseous H 2 S concentration were monitored over three months and were found to satisfy the operator's set key performance indicators. Overall, the amount of chemical required for treatment was reduced for this improved system, which substantially reduced the operator costs to treat the wells. The combination of chemistries with mutually exclusive cellular targets highlights the value of synergistic effects, specifically reducing system cost to treat while retaining low aquatic toxicity, as compared to traditional biocides used in the oilfield.

In this work, we estimate the Stimulated Original Oil In Place (SOOIP) of hydraulically fractured horizontal wells in prominent shale plays. This is done by compiling production data from hundreds of wells belonging to the Bakken, Niobrara, Wolfcamp, Eagle Ford, Bone Springs, and Woodford totaling over 2,500 wells. Additionally, we present probabilistic distributions of SOOIP with mean, standard deviation, P10, P50, and P90 estimates for each play. To circumvent the challenge of data availability for each well, we use the findings of a previous study where all reservoir unknowns are grouped into two major parameters. One of these parameters, alpha, is a function of the stimulated reservoir volume, compressibility, and pressure drawdown, where the last two are unknowns. While alpha is determined with high confidence for each well, we account for the uncertainty of compressibility and drawdown values across wells by assuming a normal distribution for these parameters. Lastly, by incorporating 1 million Monte Carlo samplings and a Mersenne Twister random number generator we estimate SOOIP distributions for each play with varying degrees of confidence. The final results show that the Niobrara and Bakken have the highest mean SOOIP values per well while the values for the Woodford and Bone Springs are the lowest among all six plays considered. Volumetric calculations using data from the literature qualitatively corroborate these findings. New insight on the stimulated volumes per well for prominent shale plays can be derived from these results as they correlate to horizontal well length, formation thickness, and hydraulic fracture half-lengths in each play.

Permian Basin reserves exceed the reserves of the largest conventional field in the world, Ghawar, Saudi Arabia [ 1 ]. To develop this field many companies use ‘factory drilling’ or ‘geometrical approach’. This approach decreases the cost of drilling and make sense for source rocks because these are hydrocarbons saturated rocks or the rocks where hydrocarbons have been cooked. Geometrical approach would be ideal for homogeneous formations, but as it will be shown below shale place are very inhomogeneous vertically and laterally. While a drilling cost for a single well is reduced, this approach significantly increases the overall development costs and environmental impact because of drilling a big number of low producing wells. We found the way to solve this problem developing a technology that uses standard open-hole log data to calculate Production Profile that shows predicted production along the entire well.

Fracture networks present a critical influence on to better assess oil recovery and to optimize production of hydraulically fractured reservoirs. We established a novel workflow for fracture uncertainty analysis and prediction, in which multiple fracture pattern realizations are created from the geostatistical analysis. The original fracture networks were created using geomechanics tools. Then the fracture network is reconstrued for uncertainty analysis and history matching. For different realizations of the fracture distributions created in this workflow, we successfully maintain the continuity of the fractures, as well as the connections from the matrix to fractures. The generated grid can be further used for treatment simulation to determine fractures geometry, height growth and respected proppant transport in the induced fracture network. In this paper, we also apply Embedded Discrete Fracture Model (EDFM) to capture the realistic geometry of fractures. Within the EDFM, each fracture plane is embedded inside the matrix grid and is discretized by the cell boundaries. We study a series of reservoir simulation realizations, in which the complex hydraulic fracture networks are created in the workflow. We investigate different fracture realizations in both planar and complex fracture configurations while maintaining the continuity within the fracture networks. This study also includes the influence of the network geometry and fractures properties on the overall performance of the reservoir. From the uncertainty analysis results, we find that the overall reservoir performance is controlled by the fracture connectivity and the distribution of conductivity within the network. A good match of production history can be achieved by adjusting the fracture connectivity. Modeling with multiple realizations of fracture networks acknowledge that a reliable production forecast is achievable using geostatistical analysis for fracture connection reconstructions. Applying Embedded Discrete Fracture Model (EDFM) on the fracture-related model simulation provides a robust and effective means of investigating multiple fracture realizations.

Scaling precipitation in the form of calcium or iron sulfate (CaSO 4 – FeSO 4 ) appears to be a common problem in most of the wells completed in the Yeso formation in the Permian Basin. Accumulation of these forms of scale in the perforations and the downhole equipment can create severe production losses and therefore they require constant, some times costly, treatments. Additionally, their presence in the wellbore hinders the efficiency of the acidizing procedures, performed by the operators to further increase the productivity of their wells. The objective of this paper is to present an innovative workflow, which significantly reduces the scaling effects and allows the acidizing of these carbonate reservoirs to be more efficient. Results are avialble for more than 20 wells, from Occidental Petroleum’s assets in the North New Mexico region. Details regarding the evolution of the procedure, the types and amounts of the chemicals are extensively discussed in this paper. The procedure starts with the candidate well selection, which preferably are located in the highest OOIP areas to maximize the efficiency. The second step involves the water sampling and analysis to determine the types of scaling and consequently the required chemical treatment. The innovation in this step has to do with the time that converters are left in the wellbore and the extra chemicals that have been added compared to the previous procedures. The last step involves the deployment of the acid downhole, where three different methodologies have been tested and evaluated based on their efficiency and well returns. The proposed approach has been successfully applied to more than 20 wells and the results are encouraging showing an average incremental oil production of ~600% while the execution cost remains very low.

Parent-child relationship is becoming a topic of high interest in the Permian Basin as more infill wells are being drilled at various times after the parent well has been produced. This paper uses an advanced modelling workflow to determine the impact of parent depletion on infill well spacing at various periods of the parent well production. As the parent well is being produced, constant well spacing based on virgin condition becomes problematic because pressure depletion around the well leads to change in stress magnitude and orientations. This change in reservoir conditions, is critical for planning infill well. Parent well depletion results in potential negative impact including: – Asymmetric fracture propagation from the child well into the depleted area around the parent well – Potential detrimental fracturing hits to the parent well These effects would potentially impair the production performance of both parent and infill wells, further reducing the overall pad efficiency of the pad completions. Parent well behavior is simulated using an unconventional fracture model (UFM), and the model is calibrated with available treating data. The resulting hydraulic fracture uses an advanced unstructured gridding algorithm that accounts for a fine complex fracture network along the lateral. A high-resolution, numerical reservoir simulator that combines the unstructured grid, rock physics, and reservoir fluid data is then used to match historical production data. The reservoir pressure depletion profile at various timesteps (6, 12, 24, and 36 months) is used as an input to calculate the resulting stress field state via a finite element model. The resulting updated geomechanical properties are used to simulate the infill well hydraulic fracture geometries at various spacing; subsequent unstructured grids are created and used to forecast production. Results are then compared to quantify the impact of depletion. – Initial reservoir pressure and horizontal stress reduce progressively with increasing time of production of the parent well; the average minimum stress change in the stimulated area reaches 18% decrease after 36 months of parent production. – Hydraulic fractures of infill wells grow preferentially towards the adjacent depleted area, reducing fracture extension in virgin rock by more than 60%. – Parent well depletion impacts fracture geometry and production performance of child wells. – Wells closer to the parent are more affected with increasing depletion time; these wells see up to 50% in production reduction as compared to the parent well. – At larger well spacing, little impact is observed due to limited interference between wells. – To help mitigate the impact of parent depletion on infill wells, an innovative spacing scheme that consists of using varying spacing on infill wells closest to the depleted parent well can be used. For this study and with current reservoir properties and completion design, if the parent well has been produced for less than 12 months, infill wells should be placed a least 750 ft away from the parent and at least 900 ft away for parent production beyond 1 year.

Although hydraulic fracturing in liquid-rich unconventional reservoirs (LUR) has become a norm, the recovery factor continues to be low. Use of enhanced oil recovery (EOR) techniques in LUR has recently become more popular to improve the recovery. The objective of this study is to numerically investigate the advantages and disadvantages of the application of the CO 2 huff-n-puff technique in LUR formations having complex fracture networks. The study explores the fluid flow mechanisms for oil recovery in a naturally fractured reservoir. A calibrated 3D mechanical earth model with geomechanical and petrophysical properties from the Eagle Ford was used for the study. A complex hydraulic fracture model was used to simulate the hydraulic fracture, proppant, and fluid distribution around the wellbore. Numerical reservoir simulation on perpendicular bisection (PEBI) grids was used to capture the permeability, porosity, and conductivity distribution due to the proppants in the hydraulic fractures. The CO 2 huff-n-puff technique using numerical reservoir simulation was used to determine the well performance and recovery factor arising from reservoir fluid viscosity reduction and gas expansion. The effect of fluid thermodynamics to recovery systems in the low-permeability reservoir medium was fully captured in this approach. An equation of state prepared for simulating the CO 2 impact on the oil was prepared with correlating the collected downhole oil sample. The numerical reservoir simulation study coupled with the complex fracture simulation model presents insights into a new means to improve the recovery factor (RF) in LUR through the injection of CO 2 . Such EOR method would be critical to increase the long-term economic benefits. The study demonstrates that that infill well requirements can be mitigated if the EOR method of huff-n-puff is utilized in cyclic modes over various time periods of production. Up to 9% extra RF was observed when the CO 2 huff-n-puff technique was used as compared to production dependent only on hydraulic fracture stimulation. Parametric sensitivity on job sizes and start timing of EOR in a producing well was used to evaluate the RF. However, the hydraulic fracture geometry and the created footprint along with the time of injection have a larger effect in improving the EOR effectiveness. The methodology demonstrates the simulation of EOR methods in unconventional reservoirs for economic assessment. The workflow demonstrates modeling CO 2 flooding as an EOR technique on the full wellbore level with complex hydraulic fracture geometry. The approach can be applied to unconventional formations in other basins to improve the recovery factor.

As a major unconventional resource play, the Williston basin contributes more than 10% of total U.S. crude oil production. Due to significant concerns about net present value and payback period, the process to select the optimum artificial lift method has always been a top priority for operators. In this case study, we investigate the potential artificial lift strategies for new wells in Williston basin. The objective is to propose an artificial lift strategy that handles the challenges associated with unconventional resources and that maximizes the asset value. In this study, a novel workflow that replaces subjective decisions with objective analysis has been applied for the process of selecting the lifting strategy that will best achieve an operator's goal based on analysis of technical criteria and economic calculated results. An initial prescreening is performed to narrow down the number of applicable artificial lift systems that will meet the technical challenges of the well. Then, the selected artificial lift methods are evaluated combining a steady state flow simulator and a reservoir model to determine the well performance and response to each lift system. This response is integrated with an economic model to determine the net present value of the proposed strategy. Different strategies and sensitivities on key parameters as oil price, expected production, and water cut are performed to determine the optimum artificial lift approach. The ability to include future well performance based on a reservoir model helps in building a strong analysis that goes beyond current well conditions and includes the changes that occur to the reservoir during the production phase, such as pressure depletion and consequent production decline. Those changes drive the need to switch from one artificial lift system to another as conditions evolve. The workflow allows the user to determine the best time to start the selected artificial lift system and the appropriate transition time to a second artificial lift method. For the Williston basin case study, only electric submersible pumps (ESP) and jet pumps (JP) can be implemented during the high-flow-rate period. As production declines, a transition to a lower-flow-rate method is required. Hydraulic rod pump systems are considered the most appropriate transition method because they make it possible to pump the required volumes from deep installations. A production forecast is combined with two different water cut scenarios to evaluate the impact on the economic results of the project. The successful use of this workflow has proven its ability to analyze the life cycle of an unconventional well and establish a process for artificial lift selection. Furthermore, the current workflow is flexible enough to be extended to other fields with different input variables.

Naturally fractured reservoirs such as the Marcellus shale require an integrated reservoir modeling approach to determine well spacing and well-to-well interference. The Marcellus Shale Energy and Environment Laboratory (MSEEL) is a joint project between universities, companies, and government to develop and test new completion technologies and acquire a robust understanding of the Marcellus shale. The study presented in this paper aims to reveal an approach to determine reservoir depletion with time through coupled geological modeling and geomechanical evaluation followed by completion and well performance history matching for a multiwell pad in the Marcellus shale. The geomechanical model was prepared with interpreted vertical log data. A discrete natural fracture (DFN) model was created and used to determine the complexity of hydraulic fracture geometry simulated through complex fracture models on a two well pad. The microseismic data obtained during the hydraulic fracture simulations served as a constraining parameter for the hydraulic fracture footprint in these wells. Sensitivity to the DFN is realized by parametric variations of DFN properties to achieve a calibrated fracture geometry. Reservoir simulation and history matching the well production data confirmed the subsurface production response to the hydraulic fractures. Well spacing sensitivity was done to reveal the optimum distance that the wells need to be spaced to maximize recovery and number of wells per section. Hydraulic fracture geometry was found to be a result of the calibration parameters, such as horizontal stress anisotropy, fracturing fluid leakoff, and the DFN. The availability of microseismic data and production history matching through integrated numerical simulation are therefore critical elements to bring unique representation of the subsurface reaction to the injected fracturing fluid. This approach can therefore be consistently applied to evaluate well spacing and interference in time for the subsequent wells completed in the Marcellus. With the current completion design and pumping treatments, the optimal well spacing of 990 ft was determined between the wells in this study. However, wells to be completed in the future need to be modeled due to the heterogeneity in the reservoir properties to ensure that wells are not either underspaced to cause well production interference or overspaced to create upswept hydrocarbon reserves in the formation. By adopting the key learnings and approach followed in this paper, operators can maximize subsurface understanding and will be able to place their wellbore in a nongeometric pattern based on reservoir heterogeneity to optimize well spacing and improve recovery.

Engineers and leaders who must decide on development strategies for unconventional resource projects face a challenging design problem. While we must make decisions on well and completion design, including well-spacing in three-dimensions, the complexity of the physical system and the interactions between these parameters can become overwhelming. The technical optimization problem can be difficult; however, asking the right questions can make the business decision clearer than it first appears. The typical approach to design optimization problems is to build models, with a tendency toward including an ever-increasing number of parameters to describe the system in exhaustive detail. However, our uncertainty in the model parameters often makes it impossible to identify the true optimum. In this work, we focus instead on reducing the number of model parameters and capturing the impact of these critical uncertainties on our business decisions. This allows us to answer the right questions in order to define and choose the best well-spacing strategy. For well-spacing optimization, a critical uncertainty is the relationship between the chosen well-spacing and the potential well-performance degradation, in terms of estimated ultimate recovery (EUR) and initial production (IP). Rather than attempting to describe fracture geometry and well interference from a mechanistic standpoint, we introduce a lumped parameter, the shared reservoir (SR) factor, to account for this complex relationship. The parameter distribution may be calibrated to (a) well results in a play, (b) well results in carefully selected analogue plays, or (c) simulated well results from probabilistic analyses. An example of a Monte-Carlo simulation using the uncertainty of the SR factor, as well as the mean EUR and IP, highlights the utility of the method. We also illustrate how the spacing decision impacts key risk and financial metrics, including the expected monetary value of the project, the probability of regretting the decision, and the probability of commercial success of the project. The shared reservoir factor is proposed to capture the complex relationships between the well-spacing decision and the EUR and IP that result from this decision. Using the shared reservoir factor, we can develop simple stochastic models to clarify an otherwise frustratingly complex optimization problem.