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Laslau Mare field is situated in the central part of the Transylvania Basin, in Romania. This is a mature gas field, composed by multi-layered sandstone reservoirs, grouped in six production packages. The permeability of the reservoirs is decreasing with depth, resulting in tight gas formations in the two deepest reservoirs. One of these tight reservoirs presents a high interest for reserves development in order to accelerate the recovery factor of the field. Compared to the other production packages, which have higher recovery factors (~80%), this package has a current RF of only 65%, with more attractive remaining recoverable gas volumes. The reservoir model was built based on 3D seismic and old log data. After history matching and simulation, a remaining gas in place map was created, in order to visualize the areas of interest for future drilling or workover operations. One new infill well was drilled in 2014, in an area with higher remaining gas in place. Special logging and side- wall coring were executed in this well, in order to get a better characterization of the reservoir properties and to build a geomechanical model for hydraulic frac design. The subject package still has a decent reservoir pressure which keeps an acceptable value of the productivity index of the producer wells. The reservoir pressure recorded after the drilling helped to update the static reservoir pressure in the area; the new points were incorporated in the dynamic model in order to get morę control in the pressure history match. New population of static properties such as: porosity, net to gross and permeability have been included in the dynamic model to generate the forecast production profile for the infill well and neighbor wells. The infill is a dual completion well which means the deeper zone produces through the tubing and the shallower zone through the annulus being separated by a packer. These two zones have two different dynamic models. The production forecasts has been done also based on decline curve analysis DCA, using historical production of the neighbor wells as a reference and the decline rate of the area, in each reservoir. In that order of ideas the infill has two gas production forecasts coming from each methodology, to compare with the real gas production, which allows us evaluating the results in the well. Based on the new data, the frac stages were defined and simulated in the deeper tight reservoir, in order to select the best target layers. The initial plan was to do multistage frac stimulation, but the idea was discarded after evaluating the operational feasibility. Ten frac stages have been evaluated creating a local refmement grid around the well and designing a fracture simulation scenario. The results pointed out one stage as being the best in terms of cumulative production and it was chosen as the only finał target for frac. A PLT log was run in the infill well for the purpose of identifying the risk of water layers and the production contribution of the perforation intervals. This was matched very well with the simulation results. The results and experience gained from this new well are helping with the further planning of the production development strategy of this production package in order to inerease the final recovery factor.
Generally, the mature fields have a good portion of the remaining reserves still trapped due to inefficient drainage, pressure decline, inerease in water cut, sand production and aging of the existing system. This paper addresses a methodology applied on the historical produetion behavior to identify techniques and initiatives to optimize the recovery factor based on redevelopment plans in a mature field. For Laslau Mare field in particular, there have been identified and implemented opportunities such as: infill drilling, work over optimization, dynamie underbalance perforation (DUP), acidizing, kick off with N2, propellant stimulation, snubbing, soaping, sand management, Wavefront Technology stimulation and wellhead and/or group compressor installation.
Content available remote Extracting subcategorisation information from Maurice Gross' grammar lexicon
Maurice Gross' grammar lexicon contains rich and exhaustive information about the morphosyntactic and semantic properties of French syntactic functors (verbs, adjectives, nouns). Yet its use within natural language processing systems is hampered both by its non standard encoding and by a structure that is partly implicit and partly underspecified. In this paper, we present a method for translating this information into a format more amenable for use by NLP systems, we discuss the results obtained so far, we compare our approach with related work and we identify the possible further uses that can be made of the reformatted information.
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