Aminfar, Ehsan (University of Calgary) | Sequera-Dalton, Belenitza (University of Calgary) | Mehta, Sudarshan Raj (University of Calgary) | Moore, Gordon (University of Calgary) | Ursenbach, Matthew (University of Calgary)
The injection of air into mature steam chambers is a promising technology to reduce the steam-to-oil-ratios (SOR) in late stages of the Steam-Assisted-Gravity-Drainage (SAGD) recovery process in Athabasca oil sand reservoirs in Alberta, Canada. Air injection allows sustaining steam chamber pressures with reduced steam injection rates. The steam capacity that becomes available due to the replacement of steam with air in mature well-pairs or pads could serve new pads optimizing steam utilization and decreasing the overall environmental footprint of the project. A novel large scale three-dimensional (3-D) physical model was designed to evaluate the prospect of the "hybrid" air and steam injection technology in a SAGD configuration utilizing up to three well-pairs. This paper discusses the 3-D model design, commissioning, experimental procedure and main results of the first tests.
For each test, the 3-D model was packed with a low oil saturation core or lean zone, representing the reservoir portion swept by steam, and a high oil saturation core or rich zone representing the un-drained zone between two coalesced steam chambers. These zones were made with preserved native "lean" and "rich" cores from Athabasca reservoirs. Once the model was packed, it was placed inside a pressure jacket where it was pressurized to reservoir pressure. Steam was injected into the model to develop a representative steam chamber in the lean zone. Once steam conditions were attained in the lean zone, steam injection was switched to air injection. Temperatures distributed in the 3-D model as well as injection and production pressures and produced gas compositions were monitored constantly and recorded during the test. Produced liquid samples were regularly captured and stored for subsequent analysis. Post-processing analyses of produced fluids and residual extracted core material allowed for determination of clean-burned zones, material balance, upgrading of the produced bitumen samples and efficiency of the process.
High peak temperatures, gas compositions, clean-burned sand in post-test cores and significant oil production indicate the development of a high temperature combustion front in the 3-D experiments. The test results confirm the injection of air into mature SAGD chambers is a very promising method not only to reduce the cumulative steam-to-oil-ratios (CSOR) and to sustain the steam chamber pressures but also to increase oil production in SAGD late life.
Intelligent multilateral well completions provide downhole flow rate, pressure, and temperature measurements at multiple well segments which allows for a continuous spatiotemporal data stream. Such an extensive data input poses a challenging task to decide on the optimal strategy of manipulating the inflow control valve (ICV) settings over time for best performance. This study investigated the use of machine learning to analyze and predict well performance given different ICV settings to ultimately maximize the well output.
A commercial reservoir simulator was used to generate two synthetic reservoir models: homogeneous (Case A) and heterogenous (Case B). These synthetic data were used to train, validate, and test machine learning models. The reservoir cases were generated based on a segmented, trilateral producer completed with three ICV devices installed at tie-in segments. The data used were measurements of wellhead and downhole flow rates across ICV segments over a period of 4,000 days. A total of 1,330 experiments were conducted with an eight-day timestep, generating a total of 667,660 sample data points for each of Case A and Case B. Fully connected neural networks were used to fit the data while model generalizability was enhanced using regularization techniques, namely L2 regularization and early stopping.
Both random sampling and Latin Hypercube Sampling (LHS) methods were evaluated in constructing the training, validation, and testing splits. Trained with different sample sizes drawn from the 1,330 simulated data histories for the two reservoir models, the proposed neural network showed excellent results. Given only ten simulated choices of ICV settings for training, the network proved capable of predicting oil and water production profiles at surface for both homogeneous and heterogeneous reservoir models with over 0.95 coefficient of determination (R2) when evaluated at unseen, test ICV settings. Extending the problem to downhole flow performance prediction, about 40 training simulated settings were necessary to achieve 0.95 R2. We observed that LHS was superior to random sampling in both R2 average and confidence interval. We also found that increasing the training and validation sample sizes increased the test R2 when testing against unseen cases. Study results suggest the applicability of machine reinforcement learning to estimate the well output at different ICV settings, where the neural network model depends fully on the real-time well feedback and production measurements.
By using a machine learning approach during the operation of a well with multiple ICV settings, it would be feasible to estimate the lateral-by-lateral output at unseen scenarios. Hence, it becomes possible to maximize the well output by using an optimization algorithm to determine the optimal ICV settings.
Africa (Sub-Sahara) Drilling began on the Bamboo-1 well, located around 35 miles offshore Cameroon in the Ntem concession. The Bamboo prospect is a basin floor fan target within an Upper Cretaceous play. The well will be drilled to an estimated depth of 4200 m. Murphy Cameroon (50%) is the operator, with partner Sterling (50%). The Nene Marine 3 exploration well--located in the Marine XII block, which is around 17 km offshore Congo--encountered a wet gas and light oil accumulation in a presalt clastic sequence Eni (65%) operates the Marine XII block, with partners New Age (25%) and Société Nationale des Pétroles du Congo (10%). CNPC said PetroChina is now building a production facility capable of pumping 4 Bcm/yr.
The strategy supports the Maximise Economic Recovery from UK Oil & Gas Strategy and Vision 2035, whose goal is to achieve £140 billion additional gross revenue from UKCS production by that time. Visuray is using its unique X-ray technology to improve downhole imaging. A company is selling a new well testing tool designed to be a cheaper, simpler way to do fiber optic sensing, and then it fades away. BP has seen enormous payoff from a program to intervene in underperforming subsea wells in the Gulf of Mexico. A coiled-tubing selective perforating and activation system that transmits critical downhole data and measurements in real time is enabling well interventions that previously could not have been executed.
Fractures can be first-order controls on fluid flow in hydrocarbon reservoirs. Understanding the characteristics of fractures such as their aperture, density, distribution, conductivity, connectivity, etc, is key for reservoir engineering and production analysis.
Well testing plays a key role in the the characterisation of fractured reservoirs, especially. New advances in the Pressure Transient Analysis (PTA) have enabled the interpretation of production data in a way where the resulting geological scenarios are in better agreement with fracture patterns observed in outcrop analogues.
Traditionally, Drill Stem Test (DST) data have been the primay source of information for well testing. However, we hypothesise that wireline conveyed tools designed for Interval Pressure Transient Testing (IPTT) could yield a more throrough description of the near-wellbore heterogeneities, including fractures.
Hence, we investigate the applicability of IPTT for characterising fractured reservoirs using detailed numerical simulations models with accurate wellbore representation to generate synthetic IPTT responses that can obtained through a next-generation wireline testing tool called SATURN. We particularly focus on cases where fractures are present in the near-wellbore region but do not intersect the wellbore. The study included parameters such as fracture densities and conductivities, distance between fractures and wellbore and the vertical extension of the fractures across geological beds.
The impact of the different fracture scenarios on the pressure transient tests was recorded as characteristic signatures on diagnostic plots (pressure derivative curves). We have called these curves "IPTT-Geotypes"; they can be used to assist the interpretation process of IPTT responses. To the best of our knowledge, this is the first time pressure derivative type curves for IPTT in fractured reservoirs are presented in the literature.
A field example of an IPTT case was analysed using the concept of geological well testing. We integrated the information from petrophysical logs and the IPTT-Geotypes to assist the calibration of a reservoir model developed to represent the geological setting of the tested reservoir interval. The results provided a sound interpretation of the reservoir geology and quantitative estimation of the matrix and fracture parameters.
The aim of this paper is to compare the performance of three horizontal infill wells in a mature field, of which one is completed with autonomous inflow control devices (AICDs). The analytic results are based on the comparison of oil production rates; water cut development and water-oil ratio plots of the wells. All the wells in this study are producing from the same homogeneous sandstone reservoir.
Two of the horizontal infill wells are targeting attic oil in an area with low risk of gas production of which one of these wells is completed with slotted liners and the other with AICDs. Both are artificially lifted with high rate electrical submersible pumps (ESPs). The third horizontal well was placed in an area with higher gas saturation, where a completion with casing, cementation and perforation was used. The performance of the horizontal wells is compared against each other.
The use of active geo-steering successfully supported the well placement into the "sweet spot" of the reservoir due to real-time well path adjustments.
It was found that the AICDs choke back a high amount of fluid and keep the water cut at a stable plateau level. This observation underlines the key benefit of using AICDs as when comparing to the other producing wells without AICDs, the water cut is steadily increasing.
Therefore the use of AICDs is a real option for horizontal well completion.
This paper will be useful to those who are in a phase of early well planning, e.g. in a field (re-)development project and have to select the best well concept (e.g. slotted liner vs. AICDs). AICDs have proven their value even in a super-mature oil field by improving production. Further advantages and challenges during operation are discussed in this paper.
Monitoring and reevaluation of petrophysical attributes in a mature field under production for many decades is crucial for optimizing production and further development planning. In this case study, a multidisciplinary approach is deployed for formation evaluation and reservoir characterization using logging-while-drilling (LWD) sensors spanning formation volumetrics, fluid analysis, high-resolution image interpretation, and geomechanics to confirm remaining oil saturations and help identify recompletion intervals. LWD technologies were used in four wells in Sahmah field of Oman to provide an integrated petrophysical and geomechanical field study using a bottomhole assembly (BHA) including gamma ray, resistivity, formation bulk density, thermal neutron, acoustic, high-resolution imaging, and formation pressure testing sensors. A deterministic multimineral petrophysical model was used to derive formation volumetrics and fluid analysis. Geomechanical interpretation used high-resolution microresistivity imaging, acoustic slownesses, and formation pressure data to verify principal stress orientations and to quantify pore pressure and horizontal minimum and maximum stress magnitudes. These data were then correlated with historical data to evaluate sweep efficiency and residual fluid saturations. LWD sensors have proven to provide robust geological, petrophysical, and geomechanical data compared to previous traditional wireline data acquisition.