We have developed a new algorithm that retrieves information about relative dip angle, relative azimuth angle, vertical resistivity, and horizontal resistivity from multicomponent EM induction logging data. To investigate how relative dip and azimuth angles affect multicomponent induction logging data, we performed a sensitivity analysis using an anisotropic whole space model. Based upon the sensitivity analysis, we designed a two‐step procedure to recover relative dip, relative azimuth, horizontal resistivity, and vertical resistivity. In the first step, the observed data are transformed into a new data set independent of the azimuth angle; a simultaneous inversion method recovers relative dip angle, vertical resistivity, and horizontal resistivity. In the second step, a 1D line search is performed to decide relative azimuth angle. Synthetic and field data tests indicate that the new inversion algorithm can extract information about relative dip and azimuth angles as well as the anisotropic resistivity structure from multicomponent induction loggingdata.

In this paper we demonstrate the advantages of a new multicomponent induction wireline instrument to measure true horizontal and vertical resistivities utilizing a field data example. These data were incorporated in an enhanced shaly sand tensor resistivity petrophysical analysis and resulted in an approximate 20% increase in calculated gas-in-place reserves over the previously used methodologies. Petrophysical results agreed well with conventional routine core analysis and production well test data. 3DEXSM Rh and Rv and conventional wireline log data were acquired in a deep marine turbidite sequence. The example well contained significant volumes of thinly bedded, laminar silty shales and high porosity gas sands that were deposited over very high quality massive channel and turbidite fan complex sands. A high anisotropy ratio, Rv/Rh, indicated the presence of high quality laminar sand pay in a 37-meter interval above the more massive gas-bearing sands. This was qualitatively confirmed by resistivity and acoustic imaging logs. The initial results of effective porosity, and effective water saturation (Indonesian) petrophysical analysis utilizing Array Laterolog deep resistivity (SFR 50–inch depth) data resulted in anomalously high water saturations and poorer apparent reservoir quality in these thinly bedded shaly sand intervals. A second analysis was performed utilizing both horizontal and vertical resistivities in a tensor resistivity model. The laminar shale volume calculated from the 3DEX resistivity data agreed well with NMR-derived shale volume from clay bound water (CBW) data. These results were used in a Thomas-Stieber volumetric model to determine the final laminar-dispersed shale distribution and laminar sand total porosity. Laminar sand resistivity was also calculated from the 3DEX horizontal and vertical resistivity data and used in a Waxman-Smits water saturation model to determine the true laminar sand water saturation. This analysis indicated that the laminar sands were generally of similar quality as the more massive sands. The tensor resistivity analysis indicated a low water saturation in the laminar sand section and is consistent with a capillary water saturation model in a dry gas reservoir. The increase in hydrocarbon saturation resulted in a significant increase in the initial GIP (Gas-In-Place) estimates. Two subsequent production well tests, comparable on a roughly equal net sand basis, choke size, and flowing tubing pressure, confirmed that the laminar sand section was capable of flowing gas at rates similar to the more massive sands without significant pressure draw down. The addition of true vertical resistivity combined with horizontal resistivity in a tensor petrophysical model provides additional new information about laminar shale volume and laminar sand resistivity in thinly bedded, hydrocarbon-bearing reservoirs. Utilizing a true volumetric petrophysical model and determining the laminar-dispersed shale distribution results in a more accurate shaly sand reservoir characterization and, as demonstrated in this example, resulted in a significant increase in hydrocarbon volume evaluated.

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