Geological effects can impact the design and successful completion of oil, gas, and geothermal wells. Understanding the stresses and pore pressures within the subsurface are important to development of a geomechanical model that can guide well design as part of an integrated process to minimize cost and maximize safety. The normals to the three orthogonal planes define a Cartesian coordinate system (x1, x2, and x3). The stress tensor has nine components, each of which has an orientation and a magnitude (see Figure 1.a). Three of these components are normal stresses, in which the force is applied perpendicular to the plane (e.g., S11 is the stress component acting normal to a plane perpendicular to the x1-axis); the other six are shear stresses, in which the force is applied along the plane in a particular direction (e.g., S12 is the force acting in the x2-direction along a plane perpendicular to the x1-axis).
The objective of the project is to reconcile and quantify the impact of geological and completion variables that cause significant EUR differences in two recent wells drilled and completed in the Uteland Butte member of the Green River formation in Uinta Basin, Utah. While the geology and reservoir conditions are similar for both wells, the completion design and parameters are different (Ball-and-Sleeve vs. Plug-and-Perf, job size, treatment rates, well length, etc.).
The Asset Team uses a structured workflow consisting of several modeling tools: Rate-Transient-Analysis (RTA), Frac Modeling (FM) and Reservoir Simulation (RS) to address and quantify the impact of each variable: Job size, Treatment Rate, Frac count per Stage, Well Length and the effect of clays.
The workflow began with a performance evaluation of the high EUR well (Plug-and-Perf, large job) with RTA and Frac modeling; followed by history-match and prediction of the EUR with the RS model. In the subsequent workflow, a single variable is changed in each modeling step, while others are held constant -- as such, the EUR impact for each variable can be quantified. The result from each step is calibrated with the actual performance observed in the field.
This model-based approach successfully quantified the production impact of each variable. Subsequently, the key drivers can be determined which explains the estimated EUR difference between the two wells. This work drives us to conclude that due to varying pressure, PVT and lithology across the field, different completion designs shall be utilized. The team has gained valuable insight on how to implement different completion techniques with varying job size and design for the basin. Currently, these results are used to drive the well designs and approval; with the long-term objective of optimizing the Field Development Plan.
You, Junyu (Petoleum Recovery Research Center) | Ampomah, William (Petoleum Recovery Research Center) | Kutsienyo, Eusebius Junior (Petoleum Recovery Research Center) | Sun, Qian (Petoleum Recovery Research Center) | Balch, Robert Scott (Petoleum Recovery Research Center) | Aggrey, Wilberforce Nkrumah (KNUST) | Cather, Martha (Petoleum Recovery Research Center)
This paper presents an optimization methodology on field-scale numerical compositional simulations of CO2 storage and production performance in the Pennsylvanian Upper Morrow sandstone reservoir in the Farnsworth Unit (FWU), Ochiltree County, Texas. This work develops an improved framework that combines hybridized machine learning algorithms for reduced order modeling and optimization techniques to co-optimize field performance and CO2 storage.
The model's framework incorporates geological, geophysical, and engineering data. We calibrated the model with the performance history of an active CO2 flood data to attain a successful history matched model. Uncertain parameters such as reservoir rock properties and relative permeability exponents were adjusted to incorporate potential changes in wettability in our history matched model.
To optimize the objective function which incorporates parameters such as oil recovery factor, CO2 storage and net present value, a proxy model was generated with hybridized multi-layer and radial basis function (RBF) Neural Network methods. To obtain a reliable and robust proxy, the proxy underwent a series of training and calibration runs, an iterative process, until the proxy model reached the specified validation criteria. Once an accepted proxy was realized, hybrid evolutionary and machine learning optimization algorithms were utilized to attain an optimum solution for pre-defined objective function. The uncertain variables and/or control variables used for the optimization study included, gas oil ratio, water alternating gas (WAG) cycle, production rates, bottom hole pressure of producers and injectors. CO2 purchased volume, and recycled gas volume in addition to placement of new infill wells were also considered in the modelling process.
The results from the sensitivity analysis reflect impacts of the control variables on the optimum results. The predictive study suggests that it is possible to develop a robust machine learning optimization algorithm that is reliable for optimizing a developmental strategy to maximize both oil production and storage of CO2 in aqueous-gaseous-mineral phases within the FWU.
This paper provides perspective on the current state of multizone completion technology and issues encountered in the industry with developing a system that offers increased capabilities to meet the increasing challenges presented by the Lower Tertiary in the Gulf of Mexico. The lower tertiary formation found in the pre-salt layers of the Gulf of Mexico has become a proving ground for extending what is possible when completing multistage fracturing in ultradeepwater wells.
This paper covers the staged field-development methodology, including analysis and evaluation of various development concepts, that enabled the company to optimize both completion design and artificial-lift selection, reducing downtime and lowering operating costs by nearly 50%. Completion engineers feel pressure to maximize production per acre and minimize the downsides of fracturing in tight spaces. Terry Palisch, talks about promoting knowledge sharing as part of JPT’s tech director report. Seismic stimulation, achievable with the implementation of a single tool, requires significantly lower investments than gas, thermal, and chemical injection methods, with minimal environmental impact. This paper describes an experimental study with a new propellant and aims to understand the pattern of fracture creation with these propellants.
The explorer has so far encountered 400 ft of reservoir pay zone in an area where it has three other producing fields. Murphy Oil to Buy Deepwater US Gulf Assets for up to $1.625 Billion The El Dorado, Arkansas-based Murphy has quickly found a home for some of the cash it will receive from the sale of its Malaysia business. The company has been rapidly expanding its US gulf footprint while simplifying its portfolio and targeting more oil. The move is part of Delek’s strategy to expand its operations beyond the Eastern Mediterranean region. Shell, meanwhile, is in the midst of a $10-billion divestment program.
Africa (Sub-Sahara) Eni announced an oil discovery in Block 15/06 offshore Angola in the Kalimba exploration prospect that is estimated to contain between 230 and 300 million bbl of light oil in place. The Kalimba-1 NFW well, which led to the discovery, is located approximately 150 km off the coast. The well was drilled in a depth of 458 m and reached a total depth of 1901 m. The data acquired in the well indicate a production capacity in excess of 5,000 B/D. The discovery creates opportunities for exploration in the southern part of Block 15/06, so far considered mainly gas-prone. The joint venture, with stakes held by Eni (operator, 36.8421%), Sonangol (36.8421%), and SSI Fifteen Limited (26.3158%), will work to appraise the updip of the discovery and will begin studies to fast-track its development.
Mogollón, J. L. (Halliburton) | Yomdo, S. (OIL India Limited) | Salazar, A. (Halliburton) | Dutta, R. (OIL India Limited) | Bobula, D. (Halliburton) | Dhodapkar, P. K. (OIL India Limited) | Lokandwala, T. (Halliburton) | Chandrasekar, V. (CMG)
The perception of better economics and less risk from infill drilling and recompletions are reasons well-focused remedies are preferred compared to reservoir-focused solutions, such as enhanced oil recovery (EOR). However, most literature does not discuss the economic and risk indicators driving this.
Using a real example, this work demonstrates that combining polymer flooding with infill drilling and recompletion substantially increases economic benefits with reasonable risk.
The reservoir considered is an Oligocene sandstone at a depth of 2700 m. The °API is 29.5 and permeability ranges from 50 to 500 mD. Current reservoir pressure is 43% of the original and it is below bubble point. A black oil model with a 133 × 56 × 128 grid was used. The model incorporated more than 50 years of matched primary and waterflooding production history and experimental polymer physico-chemical parameters. For the stochastic economic risks estimation, 1,000 iterations were run for each scenario considering uncertainties in injection-production, capital expenditures (CAPEX), operational expenditures (OPEX), and oil prices.
For a 20-year horizon, the injection-production-pressure profiles were numerically forecasted; economic results were calculated using a classic model and inputs from the forecast. The economic risk was determined stochastically. The redevelopment scenarios considered were as follows: Base: current waterflooding Existing wells interventions: workover, opening shut-in wells, and new perforations Infill drilling: vertical/horizontal infill drilling wells + existing wells operations Polymer flooding: using existing wells Combined Infill and polymer: vertical infill drilling wells and polymer flooding
Base: current waterflooding
Existing wells interventions: workover, opening shut-in wells, and new perforations
Infill drilling: vertical/horizontal infill drilling wells + existing wells operations
Polymer flooding: using existing wells
Combined Infill and polymer: vertical infill drilling wells and polymer flooding
P50 forecasts showed that interventions in existing wells in the base scenario increased oil production by 11% and net present value (NPV) by 71% with a risk index of 0.38.
A numerical optimizer was used to account for possible combinations of 14 potential drilling locations and vertical to horizontal well ratios. A scenario with three vertical wells was selected. Compared to the base case, this scenario showed an oil production increase of 23%, NPV increase of 178%, and a risk index of 0.41.
The injection rate of the polymer flood was optimized, resulting in a 17% increase in oil production and 95% increase in the NPV, with a risk index of 0.40. This justifies performing a polymer flood.
The most promising scenario is the combined infill drilling and polymer injection, which significantly improved the economic indicators—30% increase in oil production, 230% improvement of the NPV over the base scenario, with a risk index of only 0.41.
The results of this study demonstrate that the combination of EOR with different operational strategies results in significant benefits compared to the individual scenarios. Analysis of just oil production independent of economics and risk can be misleading. Infill drilling or flooding should no longer be the question. Instead, the question should be how they can be properly combined at various stages of asset life.
PY-1 is one of the few fields in India producing hydrocarbons from Fractured Basement Reservoir. The field was developed with nine slot unmanned platform with gas exported through a 56 km 4" multiphase pipeline to landfall point at Pillaperumalnallur. Field was put on production in November 2009 with three extended reach wells. The production performance of the field had some surprise and declined earlier than expected. As a result, based on the conclusions drawn from an integrated subsurface study, a two wells reentry campaign to side track wells Mercury and Earth was planned to be executed in Q1 2018. The objectives of this paper are twofold: 1. Review the production performance of a granitic basement gas field and share learnings which may be useful for similar fields being developed elsewhere.